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#P is Sandwiched by One and Two #2DNF Calls: Is Subtraction Stronger Than We Thought?
No full textInternational audienceThe canonical class in the realm of counting complexity is #P. It is well known that the problem of counting the models of a propositional formula in disjunctive normal form (#DNF) is complete for #P under Turing reductions. On the other hand, #DNF spanL and spanL #P unless NL = NP. Hence, the class of functions logspace-reducible to #DNF is a strict subset of #P under plausible complexity-theoretic assumptions. By contrast, we show that two calls to a (restricted) #2DNF oracle suffice to capture gapP, namely, that the logspace many-one closure of the subtraction between the results of two #2DNF calls is gapP. Because #P gapP, #P is strictly contained between one and two #2DNF oracle calls. Surprisingly, the propositional formulas needed in both calls are linear-time computable, and the reduction preserves interesting structural as well as symmetry properties, leading to algorithmic applications. We show that a single subtraction suffices to compensate for the absence of negation while still capturing gapP, i.e., our results carry over to the monotone fragments of #2SAT and #2DNF. Since our reduction is linear-time, it preserves sparsity and, as a consequence we obtain a sparsification lemma for both #2SAT and #2DNF. This has only been known for kSAT with k 3 and respective counting versions. We further show that both #2DNF calls can be combined into a single call if we allow a little postprocessing (computable by AC0- or TC0-circuits). Consequently, we derive refined versions of Toda's Theorem: PH [#MON2SAT] = [#MON2DNF] and PH [#IMPL2SAT]. Our route to these results is via structure-aware reductions that preserve parameters like treewidth up to an additive overhead. The absence of multiplicative overhead indeed yields parameterized SETH-tight lower bounds
Sustainable Surfactants From CNSL Waste: Oxyacetic Acid and Salt Derivatives for Formulation Applications
No full textInternational audienceABSTRACT Cashew nut shell liquid (CNSL), an abundant agro‐industrial byproduct, was valorized into nonionic and anionic surfactants. Oxyacetic acid derivatives were synthesized with high yields (94%) and assessed for their physicochemical properties. Sodium oxyacetate from crude CNSL exhibited a critical micelle concentration at 25°C (CMC) of 0.0146 wt.%, while the one from pure anacardic acid showed a CMC of 0.0468 wt.%. The hydrophilic lipophilic behavior of surfactants was quantified by determining the change of the phase inversion temperature of a reference system (PIT‐slope method). These results confirmed that the CNSL derivatives are less hydrophilic than those obtained from pure anacardic acid, likely due to the presence of cardanol‐based compounds in CNSL, which contain only a single carboxyl group. Emulsions stabilized with CNSL oxyacetic acid remained stable for over 21 days. In addition, the foaming properties of sodium oxyacetate from CNSL were comparable to those of the benchmark Texapon N70 (sodium laureth sulfate), with 73.2% foam stability after 1200 s and smaller bubble sizes at similar concentrations. These results highlight the potential of crude mixture CNSL‐derived surfactants as cost‐effective, sustainable alternatives to petrochemical surfactants for formulation applications in detergents and personal care products, contributing to waste valorization and circular economy strategies
Theoretical Study on Impact of Chemical Composition and Water Content on Mechanical Properties of Stratlingite Mineral
No full textInternational audienceStratlingite is known as one of the hydration products of aluminum-rich cements. Its microstructure and, consequently, mechanical properties, depend on the Al/Si ratio and hydration conditions. The layered structure of stratlingite is characterized as defected, with vacancies in the aluminosilicate layer. This study uses density functional theory calculations on different stratlingite models to show how chemical composition, water content, and structural defects affect its mechanical properties. The developed models represent structures with full occupancy, with little or no content of structural water, and with vacancies in the aluminosilicate layer. It was shown that the full occupancy models have the highest toughness and are strongly anisotropic. The calculated bulk modulus (BH) of the models with full occupancy was about 40 GPa, being in the typical range for calcium aluminosilicate minerals. The water loss led to an increase in BH by approximately 40% compared to the models with full occupancy. In contrast, the models with vacancies exhibited a decrease in BH of about 30%. In models with the high silicon content (Al/Si ratio of 1/4), BH, Young’s (EH), and shear (GH) moduli decreased in a range 15%–30% compared to the models with an Al/Si ratio of 2/3 of Al/Si. Finally, according to Pugh’s ratio (BH/GH), which serves as a criterion for brittle–ductile transition (1.8), the models with full occupancy exhibit a brittle behavior, whereas the defected structures are closer to ductile. This could explain the elastic behavior of stratlingite binder in concretes. Generally, the calculations showed that all investigated parameters (chemical composition, water content, and structural defects) have a significant impact on the mechanical properties of stratlingite minerals
Apport de l’intelligence artificielle pour les profils environnementaux et l’étiologie de maladies chroniques
No full textInternational audienc
Artificial Intelligence for Environmental Profiling: Improving Spatial Analysis by Capturing Local Specificities
No full textInternational audienc
Facets in Argumentation: A Formal Approach to Argument Significance
No full textInternational audienceArgumentation is a central subarea of Artificial Intelligence (AI) for modeling and reasoning about arguments. The semantics of abstract argumentation frameworks (AFs) is given by sets of arguments (extensions) and conditions on the relationship between them, such as stable or admissible. Today's solvers implement tasks such as finding extensions, deciding credulous or skeptical acceptance, counting, or enumerating extensions. While these tasks are well charted, the area between decision, counting/enumeration and fine-grained reasoning requires expensive reasoning so far. We introduce a novel concept (facets) for reasoning between decision and enumeration. Facets are arguments that belong to some extensions (credulous) but not to all extensions (skeptical). They are most natural when a user aims to navigate, filter, or comprehend the significance of specific arguments, according to their needs. We study the complexity and show that tasks involving facets are much easier than counting extensions. Finally, we provide an implementation, and conduct experiments to demonstrate feasibility
Closure-Based Tractable Possibilistic Inference from Partially Ordered DL-Lite Ontologies
No full textInternational audienceHandling partially specified inconsistent information is a major challenge, especially when balancing the richness of query answers with the need to control computational complexity. We address this challenge by proposing an efficient method for computing a consistent and enriched fragment of data, known as a repair, within knowledge bases that rely on a stable terminological component and incorporate partially ordered uncertainty in the data (ABox). Our approach, grounded in possibility theory, avoids exhaustive enumeration of conflicts or justifications by applying a positive deductive closure directly to the partially ordered ABox. This enables repair computation through simple consistency checks over data subsets, ensuring tractability while supporting an extended set of plausible inferences. Beyond this main contribution on efficient repair computation, we briefly introduce a semantic characterisation of repairs that generalises the classical notion of models for consistent knowledge bases. Finally, we present an experimental evaluation against existing possibilistic approaches, demonstrating both practical effectiveness and computational benefits
Data Handling in Python for financial analysis - Application to US technology stocks
No full textThe Case Centre, case study 125-0076-1, teaching note 125-0076-
Sovereign credit rating provision and financial development
No full textInternational audienceThis paper examines the impact of obtaining a sovereign credit rating for the first time on financial development in 50 emerging countries. Controlling for endogeneity and selection bias, we show that receiving an initial sovereign credit rating significantly transforms domestic financial systems. Rated countries experience a reallocation of bank assets, reduced reliance on domestic bank financing, and increased access to international bond markets, enabling expanded private-sector credit. Sovereign ratings also stimulate local currency bond market development and enhance foreign currency bond issuance. Additionally, they attract portfolio equity inflows and foster the internationalization of domestic banks, though their effects on direct debt flows and FDI are less pronounced. Overall, our findings highlight the critical role of sovereign credit ratings in advancing financial development and integration in emerging markets
Natural divisibility bridging convex and nonconvex technologies: Bargaining-based estimation by cost and revenue functions
No full textInternational audienceThis contribution introduces a game-theoretic framework to infer divisibility levels from observed input–output production data. This is accomplished through a new class of M-parametrized deterministic, nonparametric technologies, which extend the conventional convex (M = ) and nonconvex (M = 1) alternatives by incorporating the new notion of natural divisibility. The statistical estimation of M is rooted in a bargaining game involving two hypothetical players pursuing conflicting objectives: efficiency and divisibility, where efficiency is measured in terms of cost and revenue functions (whose value is influenced by M, whereas the divisibility is measured by M itself. We employ the Kalai–Smorodinsky bargaining solution as an axiomatic approach to achieve an equilibrium divisibility level within the M-parametrized production possibility set. We conduct numerical tests using two secondary data sources, which reveal that M = 2 is the recurrent equilibrium divisibility. This highlights a limitation of traditional convex and nonconvex frontier methods, which both ignore the need for an endogenous assessment of natural divisibility