The Fractal Dimension of SAT Formulas

Modern SAT solvers have experienced a remarkable progress on solving industrial instances. Most of the techniques have been developed after an intensive experimental testing process. Recently, there have been some attempts to analyze the structure of these formulas in terms of complex networks, with the long-term aim of explaining the success of these SAT solving techniques, and possibly improving them. We study the fractal dimension of SAT formulas, and show that most industrial families of formulas are self-similar, with a small fractal dimension. We also show that this dimension is not affected by the addition of learnt clauses. We explore how the dimension of a formula, together with other graph properties can be used to characterize SAT instances. Finally, we give empirical evidence that these graph properties can be used in state-of-the-art portfolios.Comment: 20 pages, 11 Postscript figure

Community Structure in Industrial SAT Instances

Modern SAT solvers have experienced a remarkable progress on solving industrial instances. Most of the techniques have been developed after an intensive experimental process. It is believed that these techniques exploit the underlying structure of industrial instances. However, there are few works trying to exactly characterize the main features of this structure. The research community on complex networks has developed techniques of analysis and algorithms to study real-world graphs that can be used by the SAT community. Recently, there have been some attempts to analyze the structure of industrial SAT instances in terms of complex networks, with the aim of explaining the success of SAT solving techniques, and possibly improving them. In this paper, inspired by the results on complex networks, we study the community structure, or modularity, of industrial SAT instances. In a graph with clear community structure, or high modularity, we can find a partition of its nodes into communities such that most edges connect variables of the same community. In our analysis, we represent SAT instances as graphs, and we show that most application benchmarks are characterized by a high modularity. On the contrary, random SAT instances are closer to the classical Erd\"os-R\'enyi random graph model, where no structure can be observed. We also analyze how this structure evolves by the effects of the execution of a CDCL SAT solver. In particular, we use the community structure to detect that new clauses learned by the solver during the search contribute to destroy the original structure of the formula. This is, learned clauses tend to contain variables of distinct communities

Roberto Arlt y el campo intelectual argentino de los años veinte y treinta

Abstract : Roberto Arlt and the Argentinian Intellectual Field of the 1920s and the 1930s. Taking as a basis Beatriz Sarlo and Carlos Altamirano\u27s analysis of the intellectual field (Literature and Society), inspired by Bourdieu\u27s work on the literary field, we are going to study the Argentinian intellectual field of the 1920s and the 1930s as well as the influence that Roberto Arlt had (or didn\u27t have) in this intellectual field. The writer\u27s short but prolific career —nowadays regarded as one of the greatest authors in the first half of the century— is, as a matter of fact, marked by his stormy relationship with most of the intellectual field in his days. When his misused Spanish and his use of lunfardo (slung of the slums of Buenos Aires) were censured, he, the son of immigrants, claimed his difference and vehemently criticized the ‘recognized’ authors, those who showered praise upon them and those who despised him

Agent-mediated shared conceptualizations in tagging services

Some of the most remarkable innovative technologies from the Web 2.0 are the collaborative tagging systems. They allow the use of folksonomies as a useful structure for a number of tasks in the social web, such as navigation and knowledge organization. One of the main deficiencies comes from the tagging behaviour of different users which causes semantic heterogeneity in tagging. As a consequence a user cannot benefit from the adequate tagging of others. In order to solve the problem, an agent-based reconciliation knowledge system, based on Formal Concept Analysis, is applied to facilitate the semantic interoperability between personomies. This article describes experiments that focus on conceptual structures produced by the system when it is applied to a collaborative tagging service, Delicious. Results will show the prevalence of shared tags in the sharing of common resources in the reconciliation process.Ministerio de Ciencia e Innovación TIN2009-09492Ministerio de Ciencia e Innovación TIN2010-20967-C04-0

Using the NOAA Advanced Very High Resolution Radiometer to characterise temporal and spatial trends in water temperature of large European lakes

Lakes are major repositories of biodiversity, provide multiple ecosystem services and are widely recognised as key indicators of environmental change. However, studies of lake response to drivers of change at a pan-European scale are exceptionally rare. The need for such studies has been given renewed impetus by concerns over environmental change and because of international policies, such as the EU Water Framework Directive (WFD), which impose legal obligations to monitor the condition of European lakes towards sustainable systems with good ecological status. This has highlighted the need for methods that can be widely applied across large spatial and temporal scales and produce comparable results. Remote sensing promises much in terms of information provision, but the spatial transferability and temporal repeatability of methods and relationships observed at individual or regional case studies remains unproven at the continental scale. This study demonstrates that NOAA Advanced Very High Resolution Radiometer (AVHRR) thermal data are capable of producing highly accurate (R2 &gt; 0.9) lake surface temperature (LST) estimates in lakes with variable hydromorphological characteristics and contrasting thermal regimes. Validation of the approach using archived AVHRR thermal data for Lake Geneva produced observations that were consistent with field data for equivalent time periods. This approach provides the basis for generalizing temporal and spatial trends in European lake surface temperature over several decades and confirms the potential of the full 30 year NOAA AVHRR archive to can provide AVHRR-derived LST estimates to help inform European policies on lake water quality.</p

The Impact of Implied Constraints on MaxSAT B2B Instances

The B2B scheduling optimization problem consists of finding a schedule of a set of meetings between pairs of participants, minimizing their number of idle time periods. Recent works have shown that SAT-based approaches are state-of-the-art on this problem. One interesting feature of such approaches is the use of implied constraints. In this work, we provide an experimental setting to study the impact of using these implied constraints in MaxSAT B2B instances. To this purpose and due to the reduced number of existing real-world B2B instances, we propose a random B2B instance generation model, which reproduces certain features of these problems. In our experimental analysis, we show that the impact of using some implied constraints in the MaxSAT encodings depends on the characteristics of the problem, and we also analyze the benefits of combining them. Finally, we give some insights on how a MaxSAT solver is able to exploit these implied constraints.Spanish Government RTI2018-095609-B-I00French National Research Agency (ANR) ANR-19-CHIA-0013-01Juan de la Cierva program - MCIN IJC2019040489-IAE