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1. Incremental Consistent Updating of Incomplete Databases

2. Consistent Query Answering without Repairs in Tables with Nulls and Functional Dependencies

3. Pre-, Per- and post-cooling strategies used by competitive tennis players in hot dry and hot humid conditions

4. Tables with Nulls and Functional Dependencies: Explanation and Quality of Query Answers

5. Influence of Motor Imagery Modality on First-Serve Performance in Tennis Players.

6. Four-Valued Semantics for Deductive Databases

7. Handling Inconsistencies in Tables with Nulls and Functional Dependencies

8. Managing Linked Nulls in Property Graphs: Tools to Ensure Consistency and Reduce Redundancy

10. 4-Valued Semantics Under the OWA: A Deductive Database Approach

12. Data Lakes

13. Beneficial Effects of Motor Imagery and Self-Talk on Service Performance in Skilled Tennis Players

15. A Semantic Matrix for Aggregate Query Rewriting

16. On Monotonic Deductive Database Updating Under the Open World Assumption

18. Peut-on bénéficier d’une pratique en imagerie motrice quand on a des difficultés à s’imaginer servir ?

20. Updating RDF/S Databases Under Constraints

21. Effet bénéfique d’une combinaison de feedback, d’observation et d’imagerie motrice sur la performance du départ plongé en natation

22. Hydratation quand il fait chaud : recommandations sur les boissons de l’effort au tennis

23. Les images numériques au service de l’imagerie mentale en éducation physique

26. Mining Frequent and Homogeneous Closed Itemsets

28. Influence of Face Mask and Tropical Climate on Subjective States: Affect, Motivation, and Selective Attention

29. Deductive databases in four-valued logic: rule semantics and models

31. Exploring the Impact of a Spatial Data Infrastructure on Value-Added Resellers and Vice Versa

32. Tennis Service Performance in Beginners: The Effect of Instructional Self-Talk Combined With Motor Imagery

33. Prefix based numbering schemes for XML

34. 50 ans de recherche pour le développement en Polynésie

39. Itemset-Based Variable Construction in Multi-relational Supervised Learning

40. Informative Variables Selection for Multi-relational Supervised Learning

41. Mining Frequent Disjunctive Selection Queries

47. ZLTO Interview Notes - IACS Data Re-use User Requirements

49. SEGES Interview Notes - IACS Data Re-Use User requirements

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