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1,875 results on '"Bello, Francesco"'

1. HGPflow: Extending Hypergraph Particle Flow to Collider Event Reconstruction

Author

Kakati, Nilotpal, Dreyer, Etienne, Ivina, Anna, Di Bello, Francesco Armando, Heinrich, Lukas, Kado, Marumi, and Gross, Eilam

Subjects
High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

In high energy physics, the ability to reconstruct particles based on their detector signatures is essential for downstream data analyses. A particle reconstruction algorithm based on learning hypergraphs (HGPflow) has previously been explored in the context of single jets. In this paper, we expand the scope to full proton-proton and electron-positron collision events and study reconstruction quality using metrics at the particle, jet, and event levels. Rather than operating on the entire event in a single pass, we train HGPflow on smaller partitions to avoid potentially learning long-range correlations related to the physics process. We demonstrate that this approach is feasible and that on most metrics, HGPflow outperforms both traditional particle flow algorithms and a machine learning-based benchmark model.

Published
2024

2. Urinary Diversion Versus Adverse In-Hospital Outcomes After Radical Cystectomy

Author

Rodriguez Peñaranda, Natali, di Bello, Francesco, Marmiroli, Andrea, Falkenbach, Fabian, Longoni, Mattia, Le, Quynh Chi, Goyal, Jordan A., Tian, Zhe, Saad, Fred, Shariat, Shahrokh F., Longo, Nicola, de Cobelli, Ottavio, Graefen, Markus, Briganti, Alberto, Chun, Felix K. H., Stella, Giuseppe, Piro, Adele, Puliatti, Stefano, Micali, Salvatore, and Karakiewicz, Pierre I.

Published
2025
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6. Differences in life expectancy of adrenocortical carcinoma patients vs. age‑ and sex-matched population controls

Author

Jannello, Letizia Maria Ippolita, Baudo, Andrea, Scheipner, Lukas, de Angelis, Mario, Siech, Carolin, Di Bello, Francesco, Goyal, Jordan A., Vitucci, Kira, Tian, Zhe, Luzzago, Stefano, Mistretta, Francesco A., Ferro, Matteo, Saad, Fred, Chun, Felix K. H., Briganti, Alberto, Carmignani, Luca, Longo, Nicola, de Cobelli, Ottavio, Musi, Gennaro, and Karakiewicz, Pierre I.

Published
2025
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7. Accelerating Graph-based Tracking Tasks with Symbolic Regression

Author

Soybelman, Nathalie, Schiavi, Carlo, Di Bello, Francesco A., and Gross, Eilam

Subjects
High Energy Physics - Experiment
Abstract

The reconstruction of particle tracks from hits in tracking detectors is a computationally intensive task due to the large combinatorics of detector signals. Recent efforts have proven that ML techniques can be successfully applied to the tracking problem, extending and improving the conventional methods based on feature engineering. However, complex models can be challenging to implement on heterogeneous trigger systems, integrating architectures such as FPGAs. Deploying the network on an FPGA is feasible but challenging and limited by its resources. An efficient alternative can employ symbolic regression (SR). We propose a novel approach that uses SR to replace a graph-based neural network. Substituting each network block with a symbolic function preserves the graph structure of the data and enables message passing. The technique is perfectly suitable for heterogeneous hardware, as it can be implemented more easily on FPGAs and grants faster execution times on CPU with respect to conventional methods. While the tracking problem is the target for this work, it also provides a proof-of-principle for the method that can be applied to many use cases., Comment: 15 pages, 5 figures, 1 table

Published
2024
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9. The spreading information of YouTube videos on Phosphodiesterase 5 inhibitors: a worrisome picture from one of the most consulted internet source

Author

Pezone, Gabriele, Collà Ruvolo, Claudia, Cilio, Simone, Fraia, Agostino, Di Mauro, Ernesto, Califano, Gianluigi, Passaro, Francesco, Creta, Massimiliano, Capece, Marco, La Rocca, Roberto, Celentano, Giuseppe, Morra, Simone, Di Bello, Francesco, Palmieri, Alessandro, Imbimbo, Ciro, and Longo, Nicola

Published
2024
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10. Validation of the Quality Analysis of Medical Artificial Intelligence (QAMAI) tool: a new tool to assess the quality of health information provided by AI platforms

Author

Vaira, Luigi Angelo, Lechien, Jerome R., Abbate, Vincenzo, Allevi, Fabiana, Audino, Giovanni, Beltramini, Giada Anna, Bergonzani, Michela, Boscolo-Rizzo, Paolo, Califano, Gianluigi, Cammaroto, Giovanni, Chiesa-Estomba, Carlos M., Committeri, Umberto, Crimi, Salvatore, Curran, Nicholas R., di Bello, Francesco, di Stadio, Arianna, Frosolini, Andrea, Gabriele, Guido, Gengler, Isabelle M., Lonardi, Fabio, Maglitto, Fabio, Mayo-Yáñez, Miguel, Petrocelli, Marzia, Pucci, Resi, Saibene, Alberto Maria, Saponaro, Gianmarco, Tel, Alessandro, Trabalzini, Franco, Trecca, Eleonora M. C., Vellone, Valentino, Salzano, Giovanni, and De Riu, Giacomo

Published
2024
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11. Adjuvant Systemic Therapy Improved Survival After Radical Nephroureterectomy for Upper Tract Urothelial Carcinoma

Author

Di Bello, Francesco, Jannello, Letizia Maria Ippolita, Siech, Carolin, de Angelis, Mario, Rodriguez Peñaranda, Natali, Tian, Zhe, Goyal, Jordan A., Ruvolo, Claudia Collà, Califano, Gianluigi, Creta, Massimiliano, Morra, Simone, Saad, Fred, Shariat, Shahrokh F., de Cobelli, Ottavio, Briganti, Alberto, Chun, Felix K. H., Puliatti, Stefano, Longo, Nicola, and Karakiewicz, Pierre I.

Published
2024
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12. ASO Author Reflections: Urinary Diversion and Adverse in-Hospital Outcomes After Radical Cystectomy: Contemporary Versus Historical Cohorts

Author

Rodriguez Peñaranda, Natali, Di Bello, Francesco, Marmiroli, Andrea, Falkenbach, Fabian, Longoni, Mattia, Le, Quynh Chi, Goyal, Jordan A., Tian, Zhe, Saad, Fred, Shariat, Shahrokh F., Longo, Nicola, De Cobelli, Ottavio, Graefen, Markus, Briganti, Alberto, Chun, Felix K. H., Stella, Giuseppe, Piro, Adele, Puliatti, Stefano, Micali, Salvatore, and Karakiewicz, Pierre I.

Published
2025
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13. ASO Author Reflections: History of Heart Valve Replacement: A Challenging Comorbidity for Patients Treated with Radical Nephroureterectomy

Author

Di Bello, Francesco, Rodriguez Peñaranda, Natali, Siech, Carolin, de Angelis, Mario, Tian, Zhe, Goyal, Jordan A., Collà Ruvolo, Claudia, Califano, Gianluigi, Creta, Massimiliano, Saad, Fred, Shariat, Shahrokh F., Briganti, Alberto, Chun, Felix K. H., Puliatti, Stefano, Longo, Nicola, and Karakiewicz, Pierre I.

Published
2025
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14. ASO Visual Abstract: Perioperative Complications and In-Hospital Mortality in Radical Nephroureterectomy Patients with Heart Valve Replacement

Author

Di Bello, Francesco, Rodriguez Peñaranda, Natali, Siech, Carolin, de Angelis, Mario, Tian, Zhe, Goyal, Jordan A., Collà Ruvolo, Claudia, Califano, Gianluigi, Creta, Massimiliano, Saad, Fred, Shariat, Shahrokh F., Briganti, Alberto, Chun, Felix K. H., Puliatti, Stefano, Longo, Nicola, and Karakiewicz, Pierre I.

Published
2025
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17. Radiotherapy Versus Partial Penectomy for T1 Squamous Cell Carcinoma of the Penis

Author

Jannello, Letizia Maria Ippolita, Siech, Carolin, de Angelis, Mario, Di Bello, Francesco, Rodriguez Peñaranda, Natali, Tian, Zhe, Goyal, Jordan A., Luzzago, Stefano, Mistretta, Francesco A., Montanari, Emanuele, Saad, Fred, Chun, Felix K. H., Briganti, Alberto, Micali, Salvatore, Longo, Nicola, de Cobelli, Ottavio, Musi, Gennaro, and Karakiewicz, Pierre I.

Published
2024
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18. Race/Ethnicity Affects Access and Survival Differences After Neoadjuvant or Adjuvant Chemotherapy at Radical Cystectomy in Urothelial Carcinoma Patients

Author

de Angelis, Mario, Jannello, Letizia Maria Ippolita, Siech, Carolin, Di Bello, Francesco, Peñaranda, Natali Rodriguez, Goyal, Jordan A., Tian, Zhe, Longo, Nicola, de Cobelli, Ottavio, Chun, Felix K. H., Puliatti, Stefano, Saad, Fred, Shariat, Shahrokh F., Gandaglia, Giorgio, Moschini, Marco, Montorsi, Francesco, Briganti, Alberto, and Karakiewicz, Pierre I.

Published
2024
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19. Perioperative Complications and In-Hospital Mortality in Partial and Radical Nephrectomy Patients with Heart-Valve Replacement

Author

Siech, Carolin, Baudo, Andrea, de Angelis, Mario, Jannello, Letizia Maria Ippolita, Di Bello, Francesco, Goyal, Jordan A., Tian, Zhe, Saad, Fred, Shariat, Shahrokh F., Longo, Nicola, Carmignani, Luca, de Cobelli, Ottavio, Briganti, Alberto, Kosiba, Marina, Mandel, Philipp, Kluth, Luis A., Chun, Felix K. H., and Karakiewicz, Pierre I.

Published
2024
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20. Fast Neural Network Inference on FPGAs for Triggering on Long-Lived Particles at Colliders

Author

Coccaro, Andrea, Di Bello, Francesco Armando, Giagu, Stefano, Rambelli, Lucrezia, and Stocchetti, Nicola

Subjects
High Energy Physics - Experiment, Computer Science - Machine Learning, Physics - Instrumentation and Detectors
Abstract

Experimental particle physics demands a sophisticated trigger and acquisition system capable to efficiently retain the collisions of interest for further investigation. Heterogeneous computing with the employment of FPGA cards may emerge as a trending technology for the triggering strategy of the upcoming high-luminosity program of the Large Hadron Collider at CERN. In this context, we present two machine-learning algorithms for selecting events where neutral long-lived particles decay within the detector volume studying their accuracy and inference time when accelerated on commercially available Xilinx FPGA accelerator cards. The inference time is also confronted with a CPU- and GPU-based hardware setup. The proposed new algorithms are proven efficient for the considered benchmark physics scenario and their accuracy is found to not degrade when accelerated on the FPGA cards. The results indicate that all tested architectures fit within the latency requirements of a second-level trigger farm and that exploiting accelerator technologies for real-time processing of particle-physics collisions is a promising research field that deserves additional investigations, in particular with machine-learning models with a large number of trainable parameters., Comment: 12 pages, 10 figures, 2 tables

Published
2023
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22. The prostate-gland asymmetry affects the 3- and 12-month continence recovery after RARP in patients with small prostate glands: a single center study

Author

Di Bello, Francesco, Morra, Simone, Fraia, Agostino, Pezone, Gabriele, Polverino, Federico, Granata, Giuliano, Collà Ruvolo, Claudia, Napolitano, Luigi, Ponsiglione, Andrea, Stanzione, Arnaldo, La Rocca, Roberto, Balsamo, Raffaele, Creta, Massimiliano, Imbriaco, Massimo, Imbimbo, Ciro, Longo, Nicola, and Califano, Gianluigi

Published
2024
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23. Configurable calorimeter simulation for AI applications

Author

Di Bello, Francesco Armando, Charkin-Gorbulin, Anton, Cranmer, Kyle, Dreyer, Etienne, Ganguly, Sanmay, Gross, Eilam, Heinrich, Lukas, Santi, Lorenzo, Kado, Marumi, Kakati, Nilotpal, Rieck, Patrick, and Tusoni, Matteo

Subjects
High Energy Physics - Experiment, Computer Science - Machine Learning, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract

A configurable calorimeter simulation for AI (COCOA) applications is presented, based on the Geant4 toolkit and interfaced with the Pythia event generator. This open-source project is aimed to support the development of machine learning algorithms in high energy physics that rely on realistic particle shower descriptions, such as reconstruction, fast simulation, and low-level analysis. Specifications such as the granularity and material of its nearly hermetic geometry are user-configurable. The tool is supplemented with simple event processing including topological clustering, jet algorithms, and a nearest-neighbors graph construction. Formatting is also provided to visualise events using the Phoenix event display software., Comment: 9 pages, 11 figures

Published
2023

24. ASO Author Reflections: Survival Benefit of Adjuvant Systemic Therapy After Radical Nephroureterectomy for Upper Tract Urothelial Carcinoma

Author

Di Bello, Francesco, Jannello, Letizia Maria Ippolita, Siech, Carolin, de Angelis, Mario, Rodriguez Peñaranda, Natali, Tian, Zhe, Goyal, Jordan A., Ruvolo, Claudia Collà, Califano, Gianluigi, Creta, Massimiliano, Morra, Simone, Saad, Fred, Shariat, Shahrokh F., de Cobelli, Ottavio, Briganti, Alberto, Chun, Felix K. H., Puliatti, Stefano, Longo, Nicola, and Karakiewicz, Pierre I.

Published
2024
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25. Reconstructing particles in jets using set transformer and hypergraph prediction networks

Author

Di Bello, Francesco Armando, Dreyer, Etienne, Ganguly, Sanmay, Gross, Eilam, Heinrich, Lukas, Ivina, Anna, Kado, Marumi, Kakati, Nilotpal, Santi, Lorenzo, Shlomi, Jonathan, and Tusoni, Matteo

Subjects
High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract

The task of reconstructing particles from low-level detector response data to predict the set of final state particles in collision events represents a set-to-set prediction task requiring the use of multiple features and their correlations in the input data. We deploy three separate set-to-set neural network architectures to reconstruct particles in events containing a single jet in a fully-simulated calorimeter. Performance is evaluated in terms of particle reconstruction quality, properties regression, and jet-level metrics. The results demonstrate that such a high dimensional end-to-end approach succeeds in surpassing basic parametric approaches in disentangling individual neutral particles inside of jets and optimizing the use of complementary detector information. In particular, the performance comparison favors a novel architecture based on learning hypergraph structure, HGPflow, which benefits from a physically-interpretable approach to particle reconstruction., Comment: 17 pages, 21 figures

Published
2022
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26. Set-Conditional Set Generation for Particle Physics

Author

Di Bello, Francesco Armando, Dreyer, Etienne, Ganguly, Sanmay, Gross, Eilam, Heinrich, Lukas, Kado, Marumi, Kakati, Nilotpal, Shlomi, Jonathan, and Soybelman, Nathalie

Subjects
High Energy Physics - Experiment
Abstract

The simulation of particle physics data is a fundamental but computationally intensive ingredient for physics analysis at the Large Hadron Collider, where observational set-valued data is generated conditional on a set of incoming particles. To accelerate this task, we present a novel generative model based on a graph neural network and slot-attention components, which exceeds the performance of pre-existing baselines., Comment: 10 pages, 9 figures

Published
2022
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27. Functional trait trade-offs define plant population stability across different biomes.

Author

Conti, Luisa, Valencia, Enrique, Galland, Thomas, Götzenberger, Lars, Lepš, Jan, E-Vojtkó, Anna, Carmona, Carlos, Májeková, Maria, Danihelka, Jiří, Dengler, Jürgen, Eldridge, David, Estiarte, Marc, García-González, Ricardo, Garnier, Eric, Gómez, Daniel, Hadincová, Věra, Harrison, Susan, Herben, Tomáš, Ibáñez, Ricardo, Jentsch, Anke, Juergens, Norbert, Kertész, Miklós, Klumpp, Katja, Krahulec, František, Louault, Frédérique, Marrs, Rob, Ónodi, Gábor, Pakeman, Robin, Pärtel, Meelis, Peco, Begoña, Peñuelas, Josep, Rueda, Marta, Schmidt, Wolfgang, Schmiedel, Ute, Schuetz, Martin, Skalova, Hana, Šmilauer, Petr, Šmilauerová, Marie, Smit, Christian, Song, MingHua, Stock, Martin, Val, James, Vandvik, Vigdis, Ward, David, Wesche, Karsten, Wiser, Susan, Woodcock, Ben, Young, Truman, Yu, Fei-Hai, Zobel, Martin, and de Bello, Francesco

Subjects
acquisitive, conservative, dispersal, long-term studies, temporal patterns, variability, Ecosystem, Plants, Phylogeny, Seeds, Phenotype, Plant Leaves
Abstract

Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, especially across different biomes. We compiled a worldwide collection of long-term permanent vegetation records (greater than 7000 plots from 78 datasets) from a large range of habitats which we combined with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits. We found that populations with greater leaf dry matter content and seed mass were more stable over time. Despite the variability explained by these traits being low, their effect was consistent across different datasets. Other traits played a significant, albeit weaker, role in species stability, and the inclusion of multi-variate axes or phylogeny did not substantially modify nor improve predictions. These results provide empirical evidence and highlight the relevance of specific ecological trade-offs, i.e. in different resource-use and dispersal strategies, for plant populations stability across multiple biomes. Further research is, however, necessary to integrate and evaluate the role of other specific traits, often not available in databases, and intraspecific trait variability in modulating species stability.

Published
2023

28. Clinically Meaningful Upstaging and Upgrading in Favorable Intermediate-Risk Radical Prostatectomy Patients

Author

Longoni, Mattia, Di Bello, Francesco, Rodriguez Peñaranda, Natali, Falkenbach, Fabian, Marmiroli, Andrea, Le, Quynh Chi, Tian, Zhe, Goyal, Jordan A., Longo, Nicola, Puliatti, Stefano, Graefen, Markus, de Cobelli, Ottavio, Chun, Felix K.H., Saad, Fred, Shariat, Shahrokh F., Gandaglia, Giorgio, Montorsi, Francesco, Briganti, Alberto, and Karakiewicz, Pierre I.

Published
2025
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30. Machine Learning and LHC Event Generation

Author

Butter, Anja, Plehn, Tilman, Schumann, Steffen, Badger, Simon, Caron, Sascha, Cranmer, Kyle, Di Bello, Francesco Armando, Dreyer, Etienne, Forte, Stefano, Ganguly, Sanmay, Gonçalves, Dorival, Gross, Eilam, Heimel, Theo, Heinrich, Gudrun, Heinrich, Lukas, Held, Alexander, Höche, Stefan, Howard, Jessica N., Ilten, Philip, Isaacson, Joshua, Janßen, Timo, Jones, Stephen, Kado, Marumi, Kagan, Michael, Kasieczka, Gregor, Kling, Felix, Kraml, Sabine, Krause, Claudius, Krauss, Frank, Kröninger, Kevin, Barman, Rahool Kumar, Luchmann, Michel, Magerya, Vitaly, Maitre, Daniel, Malaescu, Bogdan, Maltoni, Fabio, Martini, Till, Mattelaer, Olivier, Nachman, Benjamin, Pitz, Sebastian, Rojo, Juan, Schwartz, Matthew, Shih, David, Siegert, Frank, Stegeman, Roy, Stienen, Bob, Thaler, Jesse, Verheyen, Rob, Whiteson, Daniel, Winterhalder, Ramon, and Zupan, Jure

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Experiment
Abstract

First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range of applications of modern machine learning to event generation and simulation-based inference, including conceptional developments driven by the specific requirements of particle physics. New ideas and tools developed at the interface of particle physics and machine learning will improve the speed and precision of forward simulations, handle the complexity of collision data, and enhance inference as an inverse simulation problem., Comment: Review article based on a Snowmass 2021 contribution

Published
2022
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32. Neoadjuvant Versus Adjuvant Chemotherapy in Non-Metastatic Locally-Advanced Stage Radical Cystectomy Candidates

Author

de Angelis, Mario, Siech, Carolin, Jannello, Letizia Maria Ippolita, Bello, Francesco Di, Peñaranda, Natali Rodriguez, Goyal, Jordan A., Touma, Nawar, Tian, Zhe, Longo, Nicola, de Cobelli, Ottavio, Chun, Felix K.H., Micali, Salvatore, Saad, Fred, Shariat, Shahrokh F., Gandaglia, Giorgio, Moschini, Marco, Montorsi, Francesco, Briganti, Alberto, and Karakiewicz, Pierre I.

Published
2024
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33. Survival of Metastatic Urothelial Carcinoma of Urinary Bladder According to Number and Location of Visceral Metastases

Author

Di Bello, Francesco, de Angelis, Mario, Siech, Carolin, Jannello, Letizia Maria Ippolita, Peñaranda, Natali Rodriguez, Tian, Zhe, Goyal, Jordan A., Ruvolo, Claudia, Califano, Gianluigi, La Rocca, Roberto, Saad, Fred, Shariat, Shahrokh F., de Cobelli, Ottavio, Briganti, Alberto, Chun, Felix K.H., Puliatti, Stefano, Longo, Nicola, and Karakiewicz, Pierre I.

Published
2024
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35. Temporal Trends and Cancer-Specific Mortality in Nonmetastatic Muscle-Invasive Urothelial Carcinoma of the Urinary Bladder Treated With Trimodal Therapy

Author

de Angelis, Mario, Scheipner, Lukas, Siech, Carolin, Jannello, Letizia Maria Ippolita, Baudo, Andrea, Bello, Francesco Di, Goyal, Jordan A., Vitucci, Kira, Tian, Zhe, Longo, Nicola, Ahyai, Sascha, de Cobelli, Ottavio, Chun, Felix K.H., Saad, Fred, Shariat, Shahrokh F., Carmignani, Luca, Gandaglia, Giorgio, Moschini, Marco, Montorsi, Francesco, Briganti, Alberto, and Karakiewicz, Pierre I.

Published
2024
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36. Unmarried Status Effect on Stage at Presentation and Treatment Patterns in Non-Metastatic Upper Tract Urothelial Carcinoma Patients

Author

Morra, Simone, Scheipner, Lukas, Baudo, Andrea, Jannello, Letizia Maria Ippolita, de Angelis, Mario, Siech, Carolin, Goyal, Jordan A., Touma, Nawar, Tian, Zhe, Saad, Fred, Califano, Gianluigi, Di Bello, Francesco, La Rocca, Roberto, Ruvolo, Claudia Colla’, Mangiapia, Francesco, Shariat, Shahrokh F., Ahyai, Sascha, Carmignani, Luca, de Cobelli, Ottavio, Musi, Gennaro, Briganti, Alberto, Chun, Felix K.H., Longo, Nicola, and Karakiewicz, Pierre I.

Published
2024
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39. Perioperative complications and in-hospital mortality in radical cystectomy patients with heart-valve replacement

Author

Siech, Carolin, Baudo, Andrea, de Angelis, Mario, Jannello, Letizia Maria Ippolita, Di Bello, Francesco, Goyal, Jordan A., Tian, Zhe, Saad, Fred, Shariat, Shahrokh F., Longo, Nicola, Carmignani, Luca, de Cobelli, Ottavio, Briganti, Alberto, Kosiba, Marina, Mandel, Philipp, Kluth, Luis A., Chun, Felix K.H., and Karakiewicz, Pierre I.

Published
2024
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42. Towards a Computer Vision Particle Flow

Author

Di Bello, Francesco Armando, Ganguly, Sanmay, Gross, Eilam, Kado, Marumi, Pitt, Michael, Santi, Lorenzo, and Shlomi, Jonathan

Subjects
Physics - Data Analysis, Statistics and Probability, High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors, Statistics - Machine Learning
Abstract

In High Energy Physics experiments Particle Flow (PFlow) algorithms are designed to provide an optimal reconstruction of the nature and kinematic properties of the particles produced within the detector acceptance during collisions. At the heart of PFlow algorithms is the ability to distinguish the calorimeter energy deposits of neutral particles from those of charged particles, using the complementary measurements of charged particle tracking devices, to provide a superior measurement of the particle content and kinematics. In this paper, a computer vision approach to this fundamental aspect of PFlow algorithms, based on calorimeter images, is proposed. A comparative study of the state of the art deep learning techniques is performed. A significantly improved reconstruction of the neutral particle calorimeter energy deposits is obtained in a context of large overlaps with the deposits from charged particles. Calorimeter images with augmented finer granularity are also obtained using super-resolution techniques., Comment: 15 pages, 10 figures. Note to admin : updating to journal version

Published
2020
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44. Synchrony matters more than species richness in plant community stability at a global scale

Author

Valencia, Enrique, de Bello, Francesco, Galland, Thomas, Adler, Peter B, Lepš, Jan, E-Vojtkó, Anna, van Klink, Roel, Carmona, Carlos P, Danihelka, Jiří, Dengler, Jürgen, Eldridge, David J, Estiarte, Marc, García-González, Ricardo, Garnier, Eric, Gómez‐García, Daniel, Harrison, Susan P, Herben, Tomáš, Ibáñez, Ricardo, Jentsch, Anke, Juergens, Norbert, Kertész, Miklós, Klumpp, Katja, Louault, Frédérique, Marrs, Rob H, Ogaya, Romà, Ónodi, Gábor, Pakeman, Robin J, Pardo, Iker, Pärtel, Meelis, Peco, Begoña, Peñuelas, Josep, Pywell, Richard F, Rueda, Marta, Schmidt, Wolfgang, Schmiedel, Ute, Schuetz, Martin, Skálová, Hana, Šmilauer, Petr, Šmilauerová, Marie, Smit, Christian, Song, MingHua, Stock, Martin, Val, James, Vandvik, Vigdis, Ward, David, Wesche, Karsten, Wiser, Susan K, Woodcock, Ben A, Young, Truman P, Yu, Fei-Hai, Zobel, Martin, and Götzenberger, Lars

Subjects
Climate Change Impacts and Adaptation, Ecological Applications, Biological Sciences, Ecology, Environmental Sciences, Life Below Water, Life on Land, Carbon Sequestration, Climate Change, Ecosystem, Plant Development, Plants, Soil, evenness, climate change drivers, species richness, stability, synchrony
Abstract

The stability of ecological communities is critical for the stable provisioning of ecosystem services, such as food and forage production, carbon sequestration, and soil fertility. Greater biodiversity is expected to enhance stability across years by decreasing synchrony among species, but the drivers of stability in nature remain poorly resolved. Our analysis of time series from 79 datasets across the world showed that stability was associated more strongly with the degree of synchrony among dominant species than with species richness. The relatively weak influence of species richness is consistent with theory predicting that the effect of richness on stability weakens when synchrony is higher than expected under random fluctuations, which was the case in most communities. Land management, nutrient addition, and climate change treatments had relatively weak and varying effects on stability, modifying how species richness, synchrony, and stability interact. Our results demonstrate the prevalence of biotic drivers on ecosystem stability, with the potential for environmental drivers to alter the intricate relationship among richness, synchrony, and stability.

Published
2020

45. Neoadjuvant chemotherapy before radical cystectomy in patients with organ-confined and non-organ-confined urothelial carcinoma

Author

de Angelis, Mario, Jannello, Letizia Maria Ippolita, Siech, Carolin, Baudo, Andrea, Di Bello, Francesco, Goyal, Jordan A., Tian, Zhe, Longo, Nicola, de Cobelli, Ottavio, Chun, Felix K.H., Saad, Fred, Shariat, Shahrokh F., Carmignani, Luca, Gandaglia, Giorgio, Moschini, Marco, Montorsi, Francesco, Briganti, Alberto, and Karakiewicz, Pierre I.

Published
2025
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47. Charge collection characterisation with the Transient Current Technique of the ams H35DEMO CMOS detector after proton irradiation

Author

Anders, John, Benoit, Mathieu, Braccini, Saverio, Casanova, Raimon, Chen, Hucheng, Chen, Kai, di Bello, Francesco Armando, Fehr, Armin, Ferrere, Didier, Forshaw, Dean, Golling, Tobias, Gonzalez-Sevilla, Sergio, Iacobucci, Giuseppe, Kiehn, Moritz, Lanni, Francesco, Liu, Hongbin, Meng, Lingxin, Merlassino, Claudia, Miucci, Antonio, Nessi, Marzio, Perić, Ivan, Rimoldi, Marco, Sultan, D M S, Pinto, Mateus Vincente Barreto, Vilella, Eva, Weber, Michele, Wu, Weihao, Xu, Lailin, and Zaffaroni, Ettore

Subjects
Physics - Instrumentation and Detectors
Abstract

This paper reports on the characterisation with Transient Current Technique measurements of the charge collection and depletion depth of a radiation-hard high-voltage CMOS pixel sensor produced at ams AG. Several substrate resistivities were tested before and after proton irradiation with two different sources: the 24 GeV Proton Synchrotron at CERN and the 16.7 MeV Cyclotron at Bern Inselspital., Comment: 14 pages, 11 figures

Published
2018
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48. Performance of CMOS pixel sensor prototypes in ams H35 and aH18 technology for the ATLAS ITk upgrade

Author

Kiehn, Moritz, Di Bello, Francesco Armando, Benoit, Mathieu, Mohr, Raimon Casanova, Chen, Hucheng, Chen, Kai, S., Sultan D. M., Ehrler, Felix, Ferrere, Didier, Frizell, Dylan, Sevilla, Sergio Gonzalez, Iacobucci, Giuseppe, Lanni, Francesco, Liu, Hongbin, Merlassino, Claudia, Metcalfe, Jessica, Miucci, Antonio, Peric, Ivan, Prathapan, Mridula, Schimassek, Rudolf, Barreto, Mateus Vicente, Weston, Thomas, Figueras, Eva Vilella, Weber, Alena, Weber, Michele, Wong, Winnie, Wu, Weihao, Zaffaroni, Ettore, Zhang, Hui, and Zhang, Matt

Subjects
Physics - Instrumentation and Detectors
Abstract

Pixel sensors based on commercial high-voltage CMOS processes are an exciting technology that is considered as an option for the outer layer of the ATLAS inner tracker upgrade at the High Luminosity LHC. Here, charged particles are detected using deep n-wells as sensor diodes with the depleted region extending into the silicon bulk. Both analog and digital readout electronics can be added to achieve different levels of integration up to a fully monolithic sensor. Small scale prototypes using the ams CMOS technology have previously demonstrated that it can achieve the required radiation tolerance of $10^{15}~\text{n}_\text{eq}/\text{cm}^2$ and detection efficiencies above $99.5~\%$. Recently, large area prototypes, comparable in size to a full sensor, have been produced that include most features required towards a final design: the H35demo prototype produced in ams H35 technology that supports both external and integrated readout and the monolithic ATLASPix1 pre-production design produced in ams aH18 technology. Both chips are based on large fill-factor pixel designs, but differ in readout structure. Performance results for H35DEMO with capacitively-coupled external readout and first results for the monolithic ATLASPix1 are shown., Comment: 6 pages, 7 figures, 11th International "Hiroshima" Symposium on the Development and Application of Semiconductor Tracking Detectors (HSTD11) in conjunction with 2nd Workshop on SOI Pixel Detectors (SOIPIX2017) at OIST, Okinawa, Japan

Published
2018
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