Automated Organization ProfileICREA
ICREA
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 38.3 (sum of 39 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
A quantum system of interacting particles under the effect of a static external potential is hereby described as kicked when that potential suddenly starts moving with a constant velocity v. If initially in a stationary state, the excess energy at any time after the kick equals v⟨P⟩(t), with P being the total momentum of the system. If the system is finite and remains bound, the long time average of the excess energy tends to Mv^2, with M the system’s total mass, or a related expression if there is particle emission. Mv^2 is twice what expected from an infinitely smooth onset of motion, and any monotonic onset is expected to increase the average energy to a value within both limits. In a macroscopic system, a particle flow emerges countering the potential’s motion when the particles stay partially behind. For charged particles the described kinetic kick is equivalent to the kick given by an infinitely short electric-field pulse to the system at rest, useful as a formal limit in ultrafast phenomena. A linear-response analysis of low-v countercurrents in kicked metals shows that the coefficient of the linear term in v is the Drude weight. Non-linear in v countercurrents are expected for insulators through the electron-hole excitations induced by the kick, going as v^3 at low v for centrosymmetric ones. First-principles calculations for simple solids are used to ratify those predictions, although the findings apply more generally to systems such as Mott insulators or cold lattices of bosons or fermions.
Authors
- Santervás Arranz, Nuria ;
- Stengel, Massimiliano ;
- Artacho, Emilio
A quantum system of interacting particles under the effect of a static external potential is hereby described as kicked when that potential suddenly starts moving with a constant velocity v. If initially in a stationary state, the excess energy at any time after the kick equals v⟨P⟩(t), with P being the total momentum of the system. If the system is finite and remains bound, the long time average of the excess energy tends to Mv^2, with M the system’s total mass, or a related expression if there is particle emission. Mv^2 is twice what expected from an infinitely smooth onset of motion, and any monotonic onset is expected to increase the average energy to a value within both limits. In a macroscopic system, a particle flow emerges countering the potential’s motion when the particles stay partially behind. For charged particles the described kinetic kick is equivalent to the kick given by an infinitely short electric-field pulse to the system at rest, useful as a formal limit in ultrafast phenomena. A linear-response analysis of low-v countercurrents in kicked metals shows that the coefficient of the linear term in v is the Drude weight. Non-linear in v countercurrents are expected for insulators through the electron-hole excitations induced by the kick, going as v^3 at low v for centrosymmetric ones. First-principles calculations for simple solids are used to ratify those predictions, although the findings apply more generally to systems such as Mott insulators or cold lattices of bosons or fermions.
Authors
- Santervás Arranz, Nuria ;
- Stengel, Massimiliano ;
- Artacho, Emilio
CloudRIC is a system that meets specific reliability targets in 5G FEC processing while sharing pools of heterogeneous processors among DUs, which leads to more cost- and energy-efficient vRANs. The details of the solution are presented in CloudRIC: Open Radio Access Network (O-RAN) Virtualization with Shared Heterogeneous Computing. These repository provides a dataset, analyzed therein, with experiments carried out with different 5G LDPC decoding processors: (i) Intel FlexRAN library and two open-source alternative libraries on an Intel Xeon Gold 6240R CPU, and (ii) a proprietary driver on an NVIDIA GPU V100.See README file for a description of the dataset.
Authors
- Lo Schiavo, Leonardo ;
- Garcia-Aviles, Gines ;
- Garcia-Saavedra, Andres ;
- Gramaglia, Marco ;
- Fiore, Marco ;
- Banchs, Albert ;
- Costa-Perez, Xavier
CloudRIC is a system that meets specific reliability targets in 5G FEC processing while sharing pools of heterogeneous processors among DUs, which leads to more cost- and energy-efficient vRANs. The details of the solution are presented in CloudRIC: Open Radio Access Network (O-RAN) Virtualization with Shared Heterogeneous Computing. These repository provides a dataset, analyzed therein, with experiments carried out with different 5G LDPC decoding processors: (i) Intel FlexRAN library and two open-source alternative libraries on an Intel Xeon Gold 6240R CPU, and (ii) a proprietary driver on an NVIDIA GPU V100.See README file for a description of the dataset.
Authors
- Lo Schiavo, Leonardo ;
- Garcia-Aviles, Gines ;
- Garcia-Saavedra, Andres ;
- Gramaglia, Marco ;
- Fiore, Marco ;
- Banchs, Albert ;
- Costa-Perez, Xavier
CloudRIC is a system that meets specific reliability targets in 5G FEC processing while sharing pools of heterogeneous processors among DUs, which leads to more cost- and energy-efficient vRANs. The details of the solution are presented in https://doi.org/10.1145/3636534.3649381. These repository provides a dataset, analyzed therein, with experiments carried out with different 5G LDPC decoding processors: (i) Intel FlexRAN library and two open-source alternative libraries on an Intel Xeon Gold 6240R CPU, and (ii) a proprietary driver on an NVIDIA GPU V100.See README file for a description of the dataset.
Authors
- Lo Schiavo, Leonardo ;
- Garcia-Aviles, Gines ;
- Garcia-Saavedra, Andres ;
- Gramaglia, Marco ;
- Fiore, Marco ;
- Banchs, Albert ;
- Costa-Perez, Xavier
CloudRIC is a system that meets specific reliability targets in 5G FEC processing while sharing pools of heterogeneous processors among DUs, which leads to more cost- and energy-efficient vRANs. The details of the solution are presented in https://doi.org/10.1145/3636534.3649381. These repository provides a dataset, analyzed therein, with experiments carried out with different 5G LDPC decoding processors: (i) Intel FlexRAN library and two open-source alternative libraries on an Intel Xeon Gold 6240R CPU, and (ii) a proprietary driver on an NVIDIA GPU V100.See README file for a description of the dataset.
Authors
- Lo Schiavo, Leonardo ;
- Garcia-Aviles, Gines ;
- Garcia-Saavedra, Andres ;
- Gramaglia, Marco ;
- Fiore, Marco ;
- Banchs, Albert ;
- Costa-Perez, Xavier
Raw data from the low-magnification analysis (x35) of dental microwear of Anthracotherium sp. and Entelodon magnus from the Quercy Phosphorites formation
Authors
- Rivals, Florent
Raw data from the low-magnification analysis (x35) of dental microwear of Anthracotherium sp. and Entelodon magnus from the Quercy Phosphorites formation
Authors
- Rivals, Florent
Raw data from the low-magnification analysis (x35) of dental microwear of Anthracotherium sp. and Entelodon magnus from the Quercy Phosphorites formation
Authors
- Rivals, Florent
These is data associated with the article "Modulation of intercolumnar synchronization by endogenous electric fields in cerebral cortex" in Science Advances 2021, by the same authors.
Authors
- Rebollo, Beatriz ;
- Navarro-Guzman, Alvaro ;
- Telenczuk, Bartosz ;
- Destexhe, Alain ;
- Sanchez-Vives, Maria V.