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Shape-stabilized capric-palmitic acid/g-C3N4 composite phase change material for efficient Photothermal conversion and low-temperature heat storage
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On Extracting Legal Arguments
No full textInternational audienceBuilding on the principles of case-based reasoning, we investigate the extraction of arguments from legal case databases. An argument is modeled as a set of factors that frequently support one party (plaintiff or defendant) over the other. The relevance of an argument is assessed by the number of cases that confirm it versus those that contradict it. Following established practices in data mining, we introduce a condensed representation of arguments called closed arguments, which capture the strongest form of support given the factors they contain. We develop propositional SAT-based encodings to enable the extraction of both arguments and closed arguments using SAT solvers. Additionally, we define a more compact condensed representation called maximal arguments, which eliminates redundancy by retaining only the most informative arguments with respect to given thresholds. We propose a level-wise algorithm that builds on our SAT-based approach for argument extraction. Preliminary experiments demonstrate the feasibility of our SAT-based mining methods
Un dispositif de renforcement des littéracies universitaires via le numérique à destination d'étudiants réfugiés
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Proceedings of the 4th Workshop on the Interactions between Analogical Reasoning and Machine Learning (IARML 2025) co-located with the International Joint Conference on Artificial Intelligence (IJCAI 2025)
No full textInternational audienceAnalogical reasoning is a remarkable human capability that is used to solve hard reasoning tasks. It involves transferring knowledge from a source domain to a different but somewhat similar target domain by relying simultaneously on similarities and differences. Analogies have preoccupied humanity at least since antiquity (cf the works of Atistotle, Theon of Smyrna, among others) and have been in more recent years characterized as being "at the core of cognition" (Hofstadter 2001) showing that they permeate almost every aspect of cognition (Hofstadter and Sanders, 2013). Analogies have been tackled from various angles. Traditionally, analogical proportions, i.e., statements of the form "A is to B as C is to D", are the basis of analogical inference. They contributed to case-based reasoning and to multiple machine learning tasks such as classification, decision making and machine translation with competitive results. Also, analogical extrapolation can support dataset augmentation (analogical extension) for model learning, especially in environments with few labeled examples. Other approaches include the Structure Mapping approach of Dedre Gentner, which is based on logical descriptions (in the form of predicate-argument structures) of two domains: the more relational similarity one has between the two domains, the more analogous they can be considered. According to Hofstadter and the Fluid Analogies Research Group, analogy making is intimately related with abstraction and the search of a "common essence", which can lead to deep understanding of any concept or situation.Recent neural techniques, such as representation learning, enabled efficient approaches to detecting and solving analogies in domains where symbolic approaches had shown their limits. Transformer architectures trained using vast amounts of data have given us Large Language Models (LLMs) such as Chat-GPT, LLama and Mistral, which are capable of exhibiting human-like conversational and analogy making capacities (Webb et al. 2022). However, better evaluation metrics are needed in order to measure elusive concepts such as intelligence and understanding (Mitchel 2023). More than ever, we need to understand the role that analogies, abstraction and similarities between concepts play in language and cognition.The series of workshops Interactions between Analogical Reasoning and Machine Learning (IARML), organized on behalf of the International Joint Conferences on Artificial Intelligence (IJCAI), aims to bring together AI researchers at the crossroads of machine learning, natural language processing, knowledge representation and reasoning, who are interested in the various applications of analogical reasoning in machine learning or, conversely, of machine learning techniques to improve analogical reasoning. The first three editions were co-located with the IJCAI-ECAI 2022 (Vienna, Austria) and IJCAI 2023 (Macao, China), and IJCAI 2024 (Jeju, Korea) conferences, respectively. These first editions showed a promising impact with contributions from 5 continents, and that led to the edition of a special volume in Annals of Mathematics and Artificial Intelligence (under final reviewing), in addition to the CEUR and HAL workshop proceedings (e.g., IARML2022, IARML2023 and IARML2024). This fourth edition of the IARML workshop was hosted by the 34th International Joint Conference on Artificial Intelligence (IJCAI) and took place on August 17, 2024 in Montréal, Canada. It welcomed submissions of research papers on all topics at the intersection of analogical reasoning and machine learning. The submissions were subjected to a strict reviewing process that resulted in the selection of five original contributions, one contributed and three keynote talks:</div
Social deprivation as a key driver of spatial disparities in end-stage kidney disease incidence
No full textInternational audienceBackgroundDespite France's universal healthcare system, significant geographic disparities in the incidence of end-stage kidney disease (ESKD) persist. We hypothesized that social deprivation is a major driver of these spatial variations, independent of healthcare access and clinical risk factors, and that its contribution is stable over time.MethodsWe conducted an ecological study including 102 226 incident ESKD cases across 34 830 municipalities in metropolitan France from 2012 to 2021, using data from the national REIN (Renal Epidemiology and Information Network) registry. A Bayesian hierarchical spatiotemporal model was used to estimate the association between ESKD incidence and ecological-level covariates: social deprivation [measured by the French European Deprivation Index (EDI)], diabetes prevalence, dialysis center accessibility and long-term exposure to PM2.5 (fine particulate matter, ≤2.5 µm in diameter). We estimated the population-attributable fraction of ESKD incidence for each factor under various counterfactual scenarios.ResultsSocial deprivation was strongly associated with ESKD incidence [relative risk per 1 standard deviation increase in EDI: 1.10 (95% credible interval 1.09–1.11)] and explained 34.7% of its spatial variability. The association was only partially mediated by diabetes prevalence [mediation proportion: 15.3% (95% confidence interval 12.5–18.2)]. The model incorporating all covariates explained 49.9% of the observed spatial heterogeneity. The effect of social deprivation remained consistent over time. Reducing deprivation in the most disadvantaged areas to the levels of the 5th, 25th and 50th percentiles of less deprived areas could have prevented an estimated 23 092, 17 450 and 13 601 ESKD cases, respectively, over the study period.ConclusionsSocial deprivation is the leading ecological determinant of spatial disparities in ESKD incidence in France, with limited mediation by clinical factors and persistent effects despite universal healthcare. These findings underscore the need to address social determinants of health and to adapt kidney care delivery models to better reach socioeconomically disadvantaged populations
ON THE STRONG PERSISTENCE PROPERTY AND NORMALLY TORSION-FREENESS OF SQUARE-FREE MONOMIAL IDEALS
No full textInternational audienceIn this paper, we first show that any square-free monomial ideal in K[x1, x2, x3, x4, x5] has the strong persistence property. Next, we will provide a criterion for a minimal counterexample to the Conforti-Cornuéjols conjecture. Finally, we give a necessary and sufficient condition to determine the normally torsion-freeness of a linear combination of two normally torsion-free square-free monomial ideals.</div
Integrated Electrochemical Conversion of Plastic Waste and CO <sub>2</sub> to Formate Using Non-Noble-Metal Catalysts: <i>In Situ</i> Raman Study.
No full textInternational audiencePoly(ethylene terephthalate) (PET), a common single-use plastic, significantly contributes to CO2 emissions when discarded or incinerated. In this study, we have employed an innovative approach by combining electrochemical PET hydrolysate oxidation and CO2 reduction reaction (CO2RR) to simultaneously produce formate in a single electrochemical cell. Utilizing simple electrochemical methods, a porous 3D carbon felt (CF) electrode was anodically oxidized to produce activated carbon felt (aCF). The latter was used as a support for the electrochemical deposition of bismuth oxide carbonate (Bi2O2CO3) and nickel cobalt phosphate (NiCoPOx) for CO2RR and anodic PET hydrolysate oxidation, respectively. In situ Raman analysis indicated that MOOH (M = Ni, Co) intermediates acted as active sites for PET hydrolysate oxidation, with the ability to regenerate into lower-valence nickel species post-reaction. Both electrodes exhibited Faradaic efficiencies (FEs) exceeding 90% in their respective half-cell reactions. When implemented in a two-electrolyzer setup, a combined FE of up to 158% for both reactions was recorded at a remarkably low cell voltage of 1.8 V. This research highlights the use of non-noble metals to transform PET plastic waste and CO2 into valuable fuels
« “J’ai témoigné comme j’ai vu, comme on m’en a fait voir”. Malaquais, Journal de guerre »
No full textInternational audienceMalaquais published his Journal de guerre in 1943, then revised and extended it in the 1990s, blurring the lines between historical document and literary fiction. This article examines the conditions of its writing, publication, and reception, and offers ways to compare the two versions. The rewriting highlights Malaquais’s deep reflection on the status of the witness–a question that fundamentally shapes his literary practiceMalaquais publie en 1943 son Journal de guerre puis le reprend dans les années 1990 pour le réécrire et lui en proposer une suite, troublant les frontières entre document historique et fiction littéraire. L’articlese propose d’étudier ses conditions d’écriture, de publication et de réception et de proposer des pistes pour comparer les deux versions. La réécriture met en effet en lumière la réflexion que Malaquais propose sur le statut de témoin qui structure profondément son geste littéraire
Projet RV-REEDUC : conception, développement et évaluation d'un dispositif de réalité virtuelle pour la rééducation du membre supérieur d’enfants et d’adolescents atteints de paralysie cérébrale
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PLUMED Tutorials: A collaborative, community-driven learning ecosystem
No full textInternational audienceIn computational physics, chemistry, and biology, the implementation of new techniques in shared and open-source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several challenges. Common methods like direct knowledge transfer and in-person workshops are limited in reach and comprehensiveness. Furthermore, while the COVID-19 pandemic highlighted the benefits of online training, traditional online tutorials can quickly become outdated and may not cover all the software's functionalities. To address these issues, here we introduce "PLUMED Tutorials," a collaborative model for developing, sharing, and updating online tutorials. This initiative utilizes repository management and continuous integration to ensure compatibility with software updates. Moreover, the tutorials are interconnected to form a structured learning path and are enriched with automatic annotations to provide broader context. This paper illustrates the development, features, and advantages of PLUMED Tutorials, aiming to foster an open community for creating and sharing educational resources