A Framework for Decision-based Consistencies

International audienceConsistencies are properties of constraint networks that can be enforced by appropriate algorithms to reduce the size of the search space to be explored. Recently, many consistencies built upon taking decisions (most often, variable assignments) and stronger than (general- ized) arc consistency have been introduced. In this paper, our ambition is to present a clear picture of decision-based consistencies. We identify four general classes (or levels) of decision-based consistencies, denoted by S∆φ, E∆φ, B∆φ and D∆φ, study their relationships, and show that known consistencies are particular cases of these classes. Interestingly, this gen- eral framework provides us with a better insight into decision-based con- sistencies, and allows us to derive many new consistencies that can be directly integrated and compared with other ones

Tractable Combinations of Global Constraints

We study the complexity of constraint satisfaction problems involving global constraints, i.e., special-purpose constraints provided by a solver and represented implicitly by a parametrised algorithm. Such constraints are widely used; indeed, they are one of the key reasons for the success of constraint programming in solving real-world problems. Previous work has focused on the development of efficient propagators for individual constraints. In this paper, we identify a new tractable class of constraint problems involving global constraints of unbounded arity. To do so, we combine structural restrictions with the observation that some important types of global constraint do not distinguish between large classes of equivalent solutions.Comment: To appear in proceedings of CP'13, LNCS 8124. arXiv admin note: text overlap with arXiv:1307.179

Crossing Boundaries: Tapestry Within the Context of the 21st Century

International audienceGraphical model processing is a central problem in artificial intelligence. The optimization of the combined cost of a network of local cost functions federates a variety of famous problems including CSP, SAT and Max-SAT but also optimization in stochastic variants such as Markov Random Fields and Bayesian networks. Exact solving methods for these problems typically include branch and bound and local inference-based bounds.In this paper we are interested in understanding when and how dynamic programming based optimization can be used to efficiently enforce soft local consistencies on Global Cost Functions, defined as parameterized families of cost functions of unbounded arity. Enforcing local consistencies in cost function networks is performed by applying so-called Equivalence Preserving Transformations (EPTs) to the cost functions. These EPTs may transform global cost functions and make them intractable to optimize.We identify as tractable projection-safe those global cost functions whose optimization is and remains tractable after applying the EPTs used for enforcing arc consistency. We also provide new classes of cost functions that are tractable projection-safe thanks to dynamic programming.We show that dynamic programming can either be directly used inside filtering algorithms, defining polynomially DAG-filterable cost functions, or emulated by arc consistency filtering on a Berge-acyclic network of bounded-arity cost functions, defining Berge-acyclic network-decomposable cost functions. We give examples of such cost functions and we provide a systematic way to define decompositions from existing decomposable global constraints.These two approaches to enforcing consistency in global cost functions are then embedded in a solver for extensive experiments that confirm the feasibility and efficiency of our proposal

Jet-driven outflows of ionized gas in the nearby radio galaxy 3C 293

Fast outflows of gas, driven by the interaction between the radio jets and interstellar medium (ISM) of the host galaxy, are being observed in an increasing number of galaxies. One such example is the nearby radio galaxy 3C 293. In this paper we present integral field unit observations taken with OASIS on the William Herschel Telescope, enabling us to map the spatial extent of the ionized gas outflows across the central regions of the galaxy. The jet-driven outflow in 3C 293 is detected along the inner radio lobes with a mass outflow rate ranging from ∼0.05 to 0.17 M yr−1 (in ionized gas) and corresponding kinetic power of ∼0.5– 3.5 × 1040 erg s−1. Investigating the kinematics of the gas surrounding the radio jets (i.e. not directly associated with the outflow), we find linewidths broader than 300 km s−1 up to 5 kpc in the radial direction from the nucleus (corresponding to 3.5 kpc in the direction perpendicular to the radio axis at maximum extent). Along the axis of the radio jet linewidths >400 km s−1 are detected out to 7 kpc from the nucleus and linewidths of >500 km s−1 at a distance of 12 kpc from the nucleus, indicating that the disturbed kinematics clearly extend well beyond the high surface brightness radio structures of the jets. This is suggestive of the cocoon structure seen in simulations of jet–ISM interaction and implies that the radio jets are capable of disturbing the gas throughout the central regions of the host galaxy in all directions

The AllDifferent Constraint with Precedences

We propose ALLDIFFPREC, a new global constraint that combines together an ALLDIFFERENT constraint with precedence constraints that strictly order given pairs of variables. We identify a number of applications for this global constraint including instruction scheduling and symmetry breaking. We give an efficient propagation algorithm that enforces bounds consistency on this global constraint. We show how to implement this propagator using a decomposition that extends the bounds consistency enforcing decomposition proposed for the ALLDIFFERENT constraint. Finally, we prove that enforcing domain consistency on this global constraint is NP-hard in general

The power of propagation:when GAC is enough

Considerable effort in constraint programming has focused on the development of efficient propagators for individual constraints. In this paper, we consider the combined power of such propagators when applied to collections of more than one constraint. In particular we identify classes of constraint problems where such propagators can decide the existence of a solution on their own, without the need for any additional search. Sporadic examples of such classes have previously been identified, including classes based on restricting the structure of the problem, restricting the constraint types, and some hybrid examples. However, there has previously been no unifying approach which characterises all of these classes: structural, language-based and hybrid. In this paper we develop such a unifying approach and embed all the known classes into a common framework. We then use this framework to identify a further class of problems that can be solved by propagation alone

Palaeozoic Basement of the Pyrenees

International audienceIn the Pyrenees, the Cambrian-Lower Ordovician strata represent a quiescent time span with no remarkable tectonic activity, followed by a late Early-Mid Ordovician episode of uplift and erosion that led to the formation of the Sardic unconformity. Silurian sedimentation was widespread and transgressive followed by a Devonian succession characterized by a complex mosaic of sedi-mentary facies. Carboniferous pre-Variscan sediments (Tournaisian-Viséan cherts and limestones) precede the arrival of the synorogenic siliciclastic supplies of the Culm flysch at the Late Serpukhovian. All this succession was subsequently affected by the Serpukhovian-Bashkirian (Variscan) collision, as a result of which, the Palaeozoic rocks were incorporated into the northeastern branch of the Ibero-Armorican Arc

Anti-citrullinated peptide antibody-negative RA is a genetically distinct subset: a definitive study using only bone-erosive ACPA-negative rheumatoid arthritis

Objectives. ACPA is a highly specific marker for RA. It was recently reported that ACPA can be used to classify RA into two disease subsets, ACPA-positive and ACPA-negative RA. ACPA-positive RA was found to be associated with the HLA-DR shared epitope (SE), but ACPA negative was not. However, the suspicion remained that this result was caused by the ACPA-negative RA subset containing patients with non-RA diseases. We examined whether this is the case even when possible non-RA ACPA-negative RA patients were excluded by selecting only patients with bone erosion

A General Approach for Predicting the Filtration of Soft and Permeable Colloids: The Milk Example

Membrane filtration operations (ultra-, microfiltration) are now extensively used for concentrating or separating an ever-growing variety of colloidal dispersions. However, the phenomena that determine the efficiency of these operations are not yet fully understood. This is especially the case when dealing with colloids that are soft, deformable, and permeable. In this paper, we propose a methodology for building a model that is able to predict the performance (flux, concentration profiles) of the filtration of such objects in relation with the operating conditions. This is done by focusing on the case of milk filtration, all experiments being performed with dispersions of milk casein micelles, which are sort of ″natural″ colloidal microgels. Using this example, we develop the general idea that a filtration model can always be built for a given colloidal dispersion as long as this dispersion has been characterized in terms of osmotic pressure Π and hydraulic permeability k. For soft and permeable colloids, the major issue is that the permeability k cannot be assessed in a trivial way like in the case for hard-sphere colloids. To get around this difficulty, we follow two distinct approaches to actually measure k: a direct approach, involving osmotic stress experiments, and a reverse-calculation approach, that consists of estimating k through well-controlled filtration experiments. The resulting filtration model is then validated against experimental measurements obtained from combined milk filtration/SAXS experiments. We also give precise examples of how the model can be used, as well as a brief discussion on the possible universality of the approach presented here