STYPES: nonrecursive datalog rewriter for linear TGDs and conjunctive queries

We present STYPES, a system that rewrites ontology-mediated queries with linear tuple-generating dependencies and conjunctive queries to equivalent nonrecursive datalog (NDL) queries. The main feature of STYPES is that it produces polynomial-size rewritings whenever the treewidth of the input conjunctive queries and the size of the chases for the ontology atoms as well as their arity are bounded; moreover, the rewritings can be constructed and executed in LOGCFL, indicating high parallelisability in theory. We show experimentally that Apache Flink on a cluster of machines with 20 virtual CPUs is indeed able to parallelise execution of a series of NDL-rewritings constructed by STYPES, with the time decreasing proportionally to the number of CPUs available

Linearizing Genomes: Exact Methods and Local Search

International audienceIn this article, we address the problem of genome linearization from the perspective of Polynomial Local Search, a complexity class related to finding local optima. We prove that the linearization problem, with a neighborhood structure, the neighbor slide, is PLS-complete. On the positive side, we develop two exacts methods, one using tree decompositions with an efficient dynamic programming, the other one using an integer linear program. Finally, we compare them on real instances

Nurse scheduling via answer set programming

The Nurse Scheduling problem (NSP) is a combinatorial problem that consists of assigning nurses to shifts according to given practical constraints. In previous years, several approaches have been proposed to solve different variants of the NSP. In this paper, an ASP encoding for one of these variants is presented, whose requirements have been provided by an Italian hospital. We also design a second encoding for the computation of \ue2\u80\u9coptimal\ue2\u80\u9d schedules. Finally, an experimental analysis has been conducted on real data provided by the Italian hospital using both encodings. Results are very positive: the state-of-the-art ASP system clingo is able to compute one year schedules in few minutes, and it scales well even when more than one hundred nurses are considered

Operating Room Scheduling via Answer Set Programming

The Operating Room Scheduling (ORS) problem is the task of assigning patients to operating rooms, taking in account different specialties, the surgery and operating room shift durations and different priorities. Given that Answer Set Programming (ASP) has been recently employed for solving real-life scheduling and planning problems, in this paper we first present an off-line solution based on ASP for solving the ORS problem. Then, we present techniques for re-scheduling on-line in case the off-line schedule can not be fully applied. Results of an experimental analysis conducted on benchmarks with realistic sizes and parameters show that ASP is a suitable solving methodology also for the ORS problem

An advanced answer set programming encoding for nurse scheduling

The goal of the Nurse Scheduling Problem (NSP) is to find an assignment of nurses to shifts according to specific requirements. Given its practical relevance, many researchers have developed different strategies for solving several variants of the problem. One of such variants was recently addressed by an approach based on Answer Set Programming (ASP), obtaining promising results. Nonetheless, the original ASP encoding presents some intrinsic weaknesses, which are identified and eventually circumvented in this paper. The new encoding is designed by taking into account both intrinsic properties of NSP and internal details of ASP solvers, such as cardinality and weight constraint propagators. The performance gain of clingo and wasp is empirically verified on instances from ASP literature. As an additional contribution, the performance of clingo and wasp is compared to other declarative frameworks, namely SAT and ILP; the best performance is obtained by clingo running the new ASP encoding

Biomolecular hydration: From water dynamics to hydrodynamics

Thermally driven rotational and translational diffusion of proteins and other biomolecules is governed by frictional coupling to their solvent environment. Prediction of this coupling from biomolecular structures is a longstanding biophysical problem, which cannot be solved without knowledge of water dynamics in an interfacial region comparable to the dry protein in volume. Efficient algorithms have been developed for solving the hydrodynamic equations of motion for atomic-resolution biomolecular models, but experimental diffusion coefficients can be reproduced only by postulating hundreds of rigidly bound water molecules. This static picture of biomolecular hydration is fundamentally inconsistent with magnetic relaxation dispersion experiments and molecular dynamics simulations, which both reveal a highly dynamic interface where rotation and exchange of nearly all water molecules are several orders of magnitude faster than biomolecular diffusion. Here, we resolve this paradox by means of a dynamic hydration model that explicitly links protein hydrodynamics to hydration dynamics. With the aid of this model, bona fide structure-based predictions of global biomolecular dynamics become possible, as demonstrated here for a set of 16 proteins for which accurate experimental rotational diffusion coefficients are available

A coupled equilibrium shift mechanism in Calmodulin-Mediated signal transduction

We used nuclear magnetic resonance data to determine ensembles of conformations representing the structure and dynamics of calmodulin (CaM) in the calcium-bound state (Ca2+-CaM) and in the state bound to myosin light chain kinase (CaM-MLCK). These ensembles reveal that the Ca2+-CaM state includes a range of structures similar to those present when CaM is bound to MLCK. Detailed analysis of the ensembles demonstrates that correlated motions within the Ca2+-CaM state direct the structural fluctuations toward complex-like substates. This phenomenon enables initial ligation of MLCK at the C-terminal domain of CaM and induces a population shift among the substates accessible to the N-terminal domain, thus giving rise to the cooperativity associated with binding. Based on these results and the combination of modern free energy landscape theory with classical allostery models, we suggest that a coupled equilibrium shift mechanism controls the efficient binding of CaM to a wide range of ligands