Probabilistic Model Counting with Short XORs

The idea of counting the number of satisfying truth assignments (models) of a formula by adding random parity constraints can be traced back to the seminal work of Valiant and Vazirani, showing that NP is as easy as detecting unique solutions. While theoretically sound, the random parity constraints in that construction have the following drawback: each constraint, on average, involves half of all variables. As a result, the branching factor associated with searching for models that also satisfy the parity constraints quickly gets out of hand. In this work we prove that one can work with much shorter parity constraints and still get rigorous mathematical guarantees, especially when the number of models is large so that many constraints need to be added. Our work is based on the realization that the essential feature for random systems of parity constraints to be useful in probabilistic model counting is that the geometry of their set of solutions resembles an error-correcting code.Comment: To appear in SAT 1

Runtime Distributions and Criteria for Restarts

Randomized algorithms sometimes employ a restart strategy. After a certain number of steps, the current computation is aborted and restarted with a new, independent random seed. In some cases, this results in an improved overall expected runtime. This work introduces properties of the underlying runtime distribution which determine whether restarts are advantageous. The most commonly used probability distributions admit the use of a scale and a location parameter. Location parameters shift the density function to the right, while scale parameters affect the spread of the distribution. It is shown that for all distributions scale parameters do not influence the usefulness of restarts and that location parameters only have a limited influence. This result simplifies the analysis of the usefulness of restarts. The most important runtime probability distributions are the log-normal, the Weibull, and the Pareto distribution. In this work, these distributions are analyzed for the usefulness of restarts. Secondly, a condition for the optimal restart time (if it exists) is provided. The log-normal, the Weibull, and the generalized Pareto distribution are analyzed in this respect. Moreover, it is shown that the optimal restart time is also not influenced by scale parameters and that the influence of location parameters is only linear

An Efficient Local Search for Partial Latin Square Extension Problem

A partial Latin square (PLS) is a partial assignment of n symbols to an nxn grid such that, in each row and in each column, each symbol appears at most once. The partial Latin square extension problem is an NP-hard problem that asks for a largest extension of a given PLS. In this paper we propose an efficient local search for this problem. We focus on the local search such that the neighborhood is defined by (p,q)-swap, i.e., removing exactly p symbols and then assigning symbols to at most q empty cells. For p in {1,2,3}, our neighborhood search algorithm finds an improved solution or concludes that no such solution exists in O(n^{p+1}) time. We also propose a novel swap operation, Trellis-swap, which is a generalization of (1,q)-swap and (2,q)-swap. Our Trellis-neighborhood search algorithm takes O(n^{3.5}) time to do the same thing. Using these neighborhood search algorithms, we design a prototype iterated local search algorithm and show its effectiveness in comparison with state-of-the-art optimization solvers such as IBM ILOG CPLEX and LocalSolver.Comment: 17 pages, 2 figure

Lack of the transcription factor hypoxia-inducible factor (HIF)-1α in macrophages accelerates the necrosis of Mycobacterium avium-induced granulomas

Accepted ManuscriptThe establishment of mycobacterial infection is characterized by the formation of granulomas, which are well-organized aggregates of immune cells, namely, infected macrophages. The granuloma's main function is to constrain and prevent dissemination of the mycobacteria while focusing the immune response to a limited area. In some cases these lesions can grow progressively into large granulomas which can undergo central necrosis, thereby leading to their caseation. Macrophages are the most abundant cells present in the granuloma and are known to adapt under hypoxic conditions in order to avoid cell death. Our laboratory has developed a granuloma necrosis model that mimics the human pathology of Mycobacterium tuberculosis, using C57BL/6 mice infected intravenously with a low dose of a highly virulent strain of Mycobacterium avium. In this work, a mouse strain deleted of the hypoxia inducible factor 1a (HIF-1a) under the Cre-lox system regulated by the lysozyme M gene promoter was used to determine the relevance of HIF-1a in the caseation of granulomas. The genetic ablation of HIF-1a in the myeloid lineage causes the earlier emergence of granuloma necrosis and clearly induces an impairment of the resistance against M. avium infection coincident with the emergence of necrosis. The data provide evidence that granulomas become hypoxic before undergoing necrosis through the analysis of vascularization and quantification of HIF-1a in a necrotizing mouse model. Our results show that interfering with macrophage adaptation to hypoxia, such as through HIF-1a inactivation, accelerates granuloma necrosis.Support from national funds through FCT/MEC (Fundação para a Ciência e a Tecnologia/Ministério da Educação e Ciência), when applicable cofunded by FEDER funds within the partnership agreement PT2020 related to the research unit number 4293; from “NORTE-07-0124-FEDER-000002-Host-Pathogen Interactions,” cofunded by Programa Operacional Regional do Norte (ON.2–O Novo Norte), under the Quadro de Referência Estratégico Nacional (QREN); and from HMSP-ICT/0024/2010. T.M.S. received postdoctoral grant ON2201310 from “NORTE-07-0124-FEDER-000002-Host-Pathogen Interactions,” cofunded by Programa Operacional Regional do Norte (ON.2–O Novo Norte), under the Quadro de Referência Estratégico Nacional (QREN). M.R. received Ph.D. grant SFRH/BD/89871/2012 from FCT, Portuga

The identification of the Rosa S-locus and implications on the evolution of the Rosaceae gametophytic self-incompatibility systems

In Rosaceae species, two gametophytic self-incompatibility (GSI) mechanisms are described, the Prunus self-recognition system and the Maleae (Malus/Pyrus/Sorbus) non-self- recognition system. In both systems the pistil component is a S-RNase gene, but from two distinct phylogenetic lineages. The pollen component, always a F-box gene(s), in the case of Prunus is a single gene, and in Maleae there are multiple genes. Previously, the Rosa S-locus was mapped on chromosome 3, and three putative S-RNase genes were identified in the R. chinensis ‘Old Blush’ genome. Here, we show that these genes do not belong to the S-locus region. Using R. chinensis and R. multiflora genomes and a phylogenetic approach, we identified the S-RNase gene, that belongs to the Prunus S-lineage. Expression patterns support this gene as being the S-pistil. This gene is here also identified in R. moschata, R. arvensis, and R. minutifolia low coverage genomes, allowing the identification of positively selected amino acid sites, and thus, further supporting this gene as the S-RNase. Furthermore, genotype–phenotype association experiments also support this gene as the S-RNase. For the S-pollen GSI component we find evidence for multiple F-box genes, that show the expected expression pattern, and evidence for diversifying selection at the F-box genes within an S-haplotype. Thus, Rosa has a non-self-recognition system, like in Maleae species, despite the S-pistil gene belonging to the Prunus S-RNase lineage. These findings are discussed in the context of the Rosaceae GSI evolution. Knowledge on the Rosa S-locus has practical implications since genes controlling floral and other ornamental traits are in linkage disequilibrium with the S-locus.This work was financed by the National Funds through FCT—Fundação para a Ciência e a Tecnologia, I.P., under the project UIDB/04293/2020, and the Centre National de la Recherche Scientifique (CNRS)

Flexible constrained sampling with guarantees for pattern mining

Pattern sampling has been proposed as a potential solution to the infamous pattern explosion. Instead of enumerating all patterns that satisfy the constraints, individual patterns are sampled proportional to a given quality measure. Several sampling algorithms have been proposed, but each of them has its limitations when it comes to 1) flexibility in terms of quality measures and constraints that can be used, and/or 2) guarantees with respect to sampling accuracy. We therefore present Flexics, the first flexible pattern sampler that supports a broad class of quality measures and constraints, while providing strong guarantees regarding sampling accuracy. To achieve this, we leverage the perspective on pattern mining as a constraint satisfaction problem and build upon the latest advances in sampling solutions in SAT as well as existing pattern mining algorithms. Furthermore, the proposed algorithm is applicable to a variety of pattern languages, which allows us to introduce and tackle the novel task of sampling sets of patterns. We introduce and empirically evaluate two variants of Flexics: 1) a generic variant that addresses the well-known itemset sampling task and the novel pattern set sampling task as well as a wide range of expressive constraints within these tasks, and 2) a specialized variant that exploits existing frequent itemset techniques to achieve substantial speed-ups. Experiments show that Flexics is both accurate and efficient, making it a useful tool for pattern-based data exploration.Comment: Accepted for publication in Data Mining & Knowledge Discovery journal (ECML/PKDD 2017 journal track

Bone turnover markers for early detection of fracture healing disturbances: A review of the scientific literature

Imaging techniques are the standard method for assessment of fracture healing processes. However, these methods are perhaps not entirely reliable for early detection of complications, the most frequent of these being delayed union and non-union. A prompt diagnosis of such disorders could prevent prolonged patient distress and disability. Efforts should be directed towards the development of new technologies for improving accuracy in diagnosing complications following bone fractures. The variation in the levels of bone turnover markers (BTMs) have been assessed with regard to there ability to predict impaired fracture healing at an early stage, nevertheless the conclusions of some studies are not consensual. In this article the authors have revised the potential of BTMs as early predictors of prognosis in adult patients presenting traumatic bone fractures but who did not suffer from osteopenia or postmenopausal osteoporosis. The available information from the different studies performed in this field was systematized in order to highlight the most promising BTMs for the assessment of fracture healing outcome

Translating chitosan to clinical delivery of nucleic acid-based drugs

A number of systems based on synthetic molecules, among them cationic liposomes and poly(ethylene imine)-based polymers, have been proposed as delivery vehicles for nucleic acids. Some of these systems have even reached the market, ensuring efficient and transient transfection levels in a variety of cell types. However, toxicity issues have limited their application in vivo. In this context, chitosan, a biocompatible and biodegradable polysaccharide, has been proposed as a promising alternative for the delivery of nucleic acid-based molecules. Here we present an overview of the state of the art of chitosan-based vectors for nucleic acid delivery and the most recent data on the in vivo testing of the proposed systems. We additionally express our view on the barriers that might be hampering the translation of this knowledge into clinical practice and the challenges that need to be fulfilled for these promising vehicles to reach patients.The Programa Operacional Factores de Competitividade — COMPETE and the Portuguese funds through FCT— Fundação para a Ciência e a Tecnologia (PTDC/CTM-NAN/115124/2009 and PEst C/SAU/LA0002/2011) that supported this work. C.P.G. and C.D.F.L. acknowledge FCT for their PhD scholarships (SFRH/BD/79930/2011 and SFRH/BD/77933/2011). P.M.D.M. is supported by a Marie Curie Actions grant within the framework of the European Union’s Seventh Framework Program (PIEF-GA-2011–300485). The authors would like to thank A. Nunes (IBMC-INEB) for her contribution to the graphic design of Figure 2