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1. Action Model Learning with Guarantees

2. Safe Learning of PDDL Domains with Conditional Effects -- Extended Version

7. IgE to cyclophilins in pollen-allergic children: Epidemiologic, clinical, and diagnostic relevance of a neglected panallergen

9. Action-Failure Resilient Planning

11. A Structure-Sensitive Translation from Hybrid to Numeric Planning

12. Verification of Numeric Planning Problems Through Domain Dynamic Consistency

16. A Sound (But Incomplete) Polynomial Translation from Discretised PDDL+ to Numeric Planning

17. Genetically Driven CD39 Expression Affects Sezary Cell Viability and IL-2 Production and Detects Two Patient Subsets with Distinct Prognosis

18. Mollusk allergy in shrimp-allergic patients: Still a complex diagnosis. An Italian real-life cross-sectional multicenter study

20. Numerical Integration and Dynamic Discretization in Heuristic Search Planning over Hybrid Domains

24. The 2023 International Planning Competition

25. Using AI-Planning to Solve a Kinodynamic Path Planning Problem and Its Application for HAPS

27. A WAO — ARIA — GA2LEN consensus document on molecular-based allergy diagnosis (PAMD@): Update 2020

28. IgE allergy diagnostics and other relevant tests in allergy, a World Allergy Organization position paper

29. Mollusk allergy in shrimp-allergic patients: still a complex diagnosis. An Italian multicenter study

33. Blood and skin-derived Sezary cells: differences in proliferation-index, activation of PI3K/AKT/mTORC1 pathway and its prognostic relevance

39. ReCon: An Online Task ReConfiguration Approach for Robust Plan Execution

41. Data from CXCL13 Is Highly Produced by Sézary Cells and Enhances Their Migratory Ability via a Synergistic Mechanism Involving CCL19 and CCL21 Chemokines

42. Supplementary Table 2 from Identification of Key Regions and Genes Important in the Pathogenesis of Sézary Syndrome by Combining Genomic and Expression Microarrays

43. Supplementary Table 1 from Identification of Key Regions and Genes Important in the Pathogenesis of Sézary Syndrome by Combining Genomic and Expression Microarrays

44. Supplementary Figure 1 and Table 1 from CXCL13 Is Highly Produced by Sézary Cells and Enhances Their Migratory Ability via a Synergistic Mechanism Involving CCL19 and CCL21 Chemokines

45. Data from Identification of Key Regions and Genes Important in the Pathogenesis of Sézary Syndrome by Combining Genomic and Expression Microarrays

46. Supplementary Figure 1 from Identification of Key Regions and Genes Important in the Pathogenesis of Sézary Syndrome by Combining Genomic and Expression Microarrays

47. Supplementary Table 3 from Identification of Key Regions and Genes Important in the Pathogenesis of Sézary Syndrome by Combining Genomic and Expression Microarrays

48. Supplementary Table 4 from Identification of Key Regions and Genes Important in the Pathogenesis of Sézary Syndrome by Combining Genomic and Expression Microarrays

49. Supplementary Figure 2 from Identification of Key Regions and Genes Important in the Pathogenesis of Sézary Syndrome by Combining Genomic and Expression Microarrays

50. Genome Data Link from Identification of Key Regions and Genes Important in the Pathogenesis of Sézary Syndrome by Combining Genomic and Expression Microarrays

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