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A novel direct C7-arylation of indazoles with iodoaryls is described using Pd(OAc)2 as catalyst, 1,10-phenanthroline as ligand, and K2CO3 as base in refluxing DMA. Direct C7-arylation of 3-substituted 1H-indazole containing an EWG on the arene ring gave the expected products in good isolated yields. In addition, a one-pot Suzuki-Miyaura/arylation procedure leading to C3,C7-diarylated indazoles has been developed.

The first palladium-catalyzed oxidative alkenylation of (1H)- and (2H)-indazole derivatives with various olefins is described. The use of Pd(OAc)2 as the catalyst and Ag2CO3 as the oxidant promoted the selective C3-monoalkenylation of (1H)-indazoles and (2H)-indazoles, affording the desired products in good yields. An original oxidative C7-alkenylation of 3-substituted (1H)-indazoles was also developed. The oxidative alkenylation of (1H)-indazole was successfully applied to the total synthesis of the drug candidate gamendazole in a step- and atom-economical fashion.

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The first example of intermolecular C–H arylation of substituted 1H‐indazoles is reported. Various 1‐substituted indazoles were used as starting materials, and (hetero)aryl bromides and iodides were investigated as coupling partners. Different reaction conditions were investigated. The best results were obtained using Pd(OAc)2 as catalyst, 1,10‐phenanthroline as ligand, K2CO3 as base, and DMA as solvent. The crucial role of the ligand on the C–H arylation of substituted 1H‐indazoles is highlighted.

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An "on water" palladium-catalyzed direct (hetero)arylation of 2H-pyrazolo[3,4-b]pyridines has been developed. The reactions proceeds smoothly with at low catalytic loading at low temperature providing the C3 (hetero)arylated products in good to excellent isolated yields. Free NH 3-arylated 7-azaindazoles were also prepared by simple cleavage of the N-protected groups.

Fog Computing has emerged as a virtual platform extending Cloud services down to the network edge especially (and not exclusively) to host IoT applications. Data replication strategies have been designed to investigate the best storage location of data copies in geo-distributed storage systems in order to reduce its access time for different consumer services spread over the infrastructure. Unfortunately, due to the geographical distance between Fog nodes, misplacing data in such an infrastructure may generate high latencies when accessing or synchronizing replicas, thus degrading the Quality of Service (QoS). In this paper, we present two strategies to manage IoT data replication and consistency in Fog infrastructures. Our strategies choose for each datum, the right replica number and their location in order to reduce data access latency and replicas synchronization cost. This is done while respecting the required consistency