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1. Optimizing Quantile-based Trading Strategies in Electricity Arbitrage

Author

O'Connor, Ciaran, Collins, Joseph, Prestwich, Steven, and Visentin, Andrea

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Efficiently integrating renewable resources into electricity markets is vital for addressing the challenges of matching real-time supply and demand while reducing the significant energy wastage resulting from curtailments. To address this challenge effectively, the incorporation of storage devices can enhance the reliability and efficiency of the grid, improving market liquidity and reducing price volatility. In short-term electricity markets, participants navigate numerous options, each presenting unique challenges and opportunities, underscoring the critical role of the trading strategy in maximizing profits. This study delves into the optimization of day-ahead and balancing market trading, leveraging quantile-based forecasts. Employing three trading approaches with practical constraints, our research enhances forecast assessment, increases trading frequency, and employs flexible timestamp orders. Our findings underscore the profit potential of simultaneous participation in both day-ahead and balancing markets, especially with larger battery storage systems; despite increased costs and narrower profit margins associated with higher-volume trading, the implementation of high-frequency strategies plays a significant role in maximizing profits and addressing market challenges. Finally, we modelled four commercial battery storage systems and evaluated their economic viability through a scenario analysis, with larger batteries showing a shorter return on investment.

Published
2024

2. Outcomes in high-risk subgroups after fixed-duration ibrutinib + venetoclax for chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL): Up to 5.5 years of follow-up in the phase 2 CAPTIVATE study.

Author

Wierda, William G, Jacobs, Ryan, Barr, Paul M, Allan, John N, Siddiqi, Tanya, Tedeschi, Alessandra, Kipps, Thomas J, O'Brien, Susan Mary, Badoux, Xavier C, Visentin, Andrea, Lasica, Masa, Carney, Dennis, Elinder Camburn, Anna, De La Serna Torroba, Javier, Szafer-Glusman, Edith, Zhou, Cathy, Szoke, Anita, Dean, James P, Ghia, Paolo, and Tam, Constantine S

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Clinical Research, Lymphoma, Biotechnology, Cancer Genomics, Hematology, Precision Medicine, Genetics, Cancer, Clinical Trials and Supportive Activities, Lymphatic Research, Minority Health, Rare Diseases, Human Genome, 6.1 Pharmaceuticals, Clinical Sciences, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

7009 Background: The phase 2 CAPTIVATE study evaluated first-line ibrutinib (Ibr) + venetoclax (Ven) for CLL/SLL in 2 cohorts: minimal residual disease (MRD)-guided randomized discontinuation (MRD cohort) and Fixed Duration (FD cohort). Ibr±Ven retreatment was allowed in patients (pts) who had progressive disease (PD). Here, we report outcomes for pts with high-risk genomic features from the FD cohort and retreatment outcomes in pts from the FD cohort and MRD cohort placebo arm. Methods: Pts aged ≤70 y with previously untreated CLL/SLL without restriction on genomic risk factors received 3 cycles of Ibr, then 12 cycles of Ibr+Ven (Ibr, 420 mg/d orally; Ven, 5-wk ramp up to 400 mg/d orally). On-study retreatment included single-agent Ibr (FD cohort or MRD cohort placebo arm); pts with PD >2 y after end of treatment (EOT) could be retreated with FD Ibr+Ven (FD cohort). Results: In the FD cohort (n=159) with a median follow-up of 61.2 mo (range, 0.8–66.3), 5-y PFS and OS rates (95% CI) were 67% (59–74) and 96% (91–98), respectively. 5-y PFS rates were higher in pts with undetectable MRD at 3 mo after EOT in peripheral blood (83%) or bone marrow (84%) vs those without (48% and 50%, respectively). 5-y PFS rates (95% CI) in pts with genomic risk factors were: del(17p)/mutated TP53 41% (21–59), complex karyotype 57% (37–72), del(11q) 64% (30–85), and unmutated IGHV 68% (50–80) (Table). In total, 18 second malignancies occurred in 13 pts (10 events in 8 pts during FD Ibr+Ven, 6 events in 4 pts after EOT and before retreatment, and 2 events in 2 pts during retreatment). Of 202 pts who completed Ibr+Ven (FD cohort, n=159; MRD cohort placebo arm, n=43), 63 have had PD to date; PD occurred >2 y after EOT in 43/63 pts (68%). 32/63 (51%) pts initiated retreatment with Ibr (n=25) or Ibr+Ven (n=7). With a median time on Ibr retreatment of 21.9 mo (range, 0.03–50.4), ORR was 86% in 22 evaluable pts (best response: 1 CR; 1 nodular PR; 17 PR; 2 SD; 1 PD [Richter transformation]). With a median time on Ibr+Ven retreatment of 13.8 mo (range, 3.7–15.1), ORR was 71% in 7 evaluable pts (best response: 1 CR; 4 PR; 1 PR with lymphocytosis; 1 SD). Conclusions: With up to 5.5 y of follow-up, FD Ibr+Ven continues to provide clinically meaningful PFS in pts with high-risk genomic features, as well as in the overall population. Ibr-based retreatment provides promising responses in pts needing subsequent therapy after the all-oral FD regimen of Ibr+Ven. Clinical trial information: NCT02910583 . [Table: see text]

Published
2024

3. Electricity Price Forecasting in the Irish Balancing Market

Author

O'Connor, Ciaran, Collins, Joseph, Prestwich, Steven, and Visentin, Andrea

Subjects
Computer Science - Machine Learning, Quantitative Finance - Pricing of Securities
Abstract

Short-term electricity markets are becoming more relevant due to less-predictable renewable energy sources, attracting considerable attention from the industry. The balancing market is the closest to real-time and the most volatile among them. Its price forecasting literature is limited, inconsistent and outdated, with few deep learning attempts and no public dataset. This work applies to the Irish balancing market a variety of price prediction techniques proven successful in the widely studied day-ahead market. We compare statistical, machine learning, and deep learning models using a framework that investigates the impact of different training sizes. The framework defines hyperparameters and calibration settings; the dataset and models are made public to ensure reproducibility and to be used as benchmarks for future works. An extensive numerical study shows that well-performing models in the day-ahead market do not perform well in the balancing one, highlighting that these markets are fundamentally different constructs. The best model is LEAR, a statistical approach based on LASSO, which outperforms more complex and computationally demanding approaches.

Published
2024

5. Explainable Algorithm Selection for the Capacitated Lot Sizing Problem

Author

Visentin, Andrea, Gallchóir, Aodh Ó, Kärcher, Jens, Meyr, Herbert, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, and Dilkina, Bistra, editor

Published
2024
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6. Clustering-Based Numerosity Reduction for Cloud Workload Forecasting

Author

Rossi, Andrea, Visentin, Andrea, Prestwich, Steven, Brown, Kenneth N., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chatzigiannakis, Ioannis, editor, and Karydis, Ioannis, editor

Published
2024
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8. Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Transfer Learning

Author

Rossi, Andrea, Visentin, Andrea, Carraro, Diego, Prestwich, Steven, and Brown, Kenneth N.

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Predicting future resource demand in Cloud Computing is essential for optimizing the trade-off between serving customers' requests efficiently and minimizing the provisioning cost. Modelling prediction uncertainty is also desirable to better inform the resource decision-making process, but research in this field is under-investigated. In this paper, we propose univariate and bivariate Bayesian deep learning models that provide predictions of future workload demand and its uncertainty. We run extensive experiments on Google and Alibaba clusters, where we first train our models with datasets from different cloud providers and compare them with LSTM-based baselines. Results show that modelling the uncertainty of predictions has a positive impact on performance, especially on service level metrics, because uncertainty quantification can be tailored to desired target service levels that are critical in cloud applications. Moreover, we investigate whether our models benefit transfer learning capabilities across different domains, i.e. dataset distributions. Experiments on the same workload datasets reveal that acceptable transfer learning performance can be achieved within the same provider (because distributions are more similar). Also, domain knowledge does not transfer when the source and target domains are very different (e.g. from different providers), but this performance degradation can be mitigated by increasing the training set size of the source domain.

Published
2023

10. SATfeatPy -- A Python-based Feature Extraction System for Satisfiability

Author

Provan-Bessell, Benjamin, Dalla, Marco, Visentin, Andrea, and O'Sullivan, Barry

Subjects
Computer Science - Artificial Intelligence
Abstract

Feature extraction is a fundamental task in the application of machine learning methods to SAT solving. It is used in algorithm selection and configuration for solver portfolios and satisfiability classification. Many approaches have been proposed to extract meaningful attributes from CNF instances. Most of them lack a working/updated implementation, and the limited descriptions lack clarity affecting the reproducibility. Furthermore, the literature misses a comparison among the features. This paper introduces SATfeatPy, a library that offers feature extraction techniques for SAT problems in the CNF form. This package offers the implementation of all the structural and statistical features from there major papers in the field. The library is provided in an up-to-date, easy-to-use Python package alongside a detailed feature description. We show the high accuracy of SAT/UNSAT and problem category classification, using five sets of features generated using our library from a dataset of 3000 SAT and UNSAT instances, over ten different classes of problems. Finally, we compare the usefulness of the features and importance for predicting a SAT instance's original structure in an ablation study., Comment: 8 pages, 2 figures, code available at https://github.com/bprovanbessell/SATfeatPy

Published
2022

11. Leukemic cell-secreted interleukin-9 suppresses cytotoxic T cell-mediated killing in chronic lymphocytic leukemia

Author

Boncompagni, Gioia, Tatangelo, Vanessa, Lopresti, Ludovica, Ulivieri, Cristina, Capitani, Nagaja, Tangredi, Carmela, Finetti, Francesca, Marotta, Giuseppe, Frezzato, Federica, Visentin, Andrea, Ciofini, Sara, Gozzetti, Alessandro, Bocchia, Monica, Calzada-Fraile, Diego, Martin Cofreces, Noa B., Trentin, Livio, Patrussi, Laura, and Baldari, Cosima T.

Published
2024
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13. Stochastic Dynamic Programming Heuristic for the (R, s, S) Policy Parameters Computation

Author

Visentin, Andrea, Prestwich, Steven, Rossi, Roberto, and Tarim, S. Armagan

Subjects
Mathematics - Optimization and Control
Abstract

The (R, s, S) is a stochastic inventory control policy widely used by practitioners. In an inventory system managed according to this policy, the inventory is reviewed at instant R; if the observed inventory position is lower than the reorder level s an order is placed. The order's quantity is set to raise the inventory position to the order-up-to-level S. This paper introduces a new stochastic dynamic program (SDP) based heuristic to compute the (R, s, S) policy parameters for the non-stationary stochastic lot-sizing problem with backlogging of the excessive demand, fixed order and review costs, and linear holding and penalty costs. In a recent work, Visentin et al. (2021) present an approach to compute optimal policy parameters under these assumptions. Our model combines a greedy relaxation of the problem with a modified version of Scarf's (s, S) SDP. A simple implementation of the model requires a prohibitive computational effort to compute the parameters. However, we can speed up the computations by using K-convexity property and memorisation techniques. The resulting algorithm is considerably faster than the state-of-the-art, extending its adoptability by practitioners. An extensive computational study compares our approach with the algorithms available in the literature.

Published
2022
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19. Computing Optimal (R, s, S) Policy Parameters by a Hybrid of Branch-and-Bound and Stochastic Dynamic Programming

Author

Visentin, Andrea, Prestwich, Steven, Rossi, Roberto, and Tarim, S. Armagan

Subjects
Mathematics - Optimization and Control
Abstract

A well-know control policy in stochastic inventory control is the (R, s, S) policy, in which inventory is raised to an order-up-to-level S at a review instant R whenever it falls below reorder-level s. To date, little or no work has been devoted to developing approaches for computing (R, s, S) policy parameters. In this work, we introduce a hybrid approach that exploits tree search to compute optimal replenishment cycles, and stochastic dynamic programming to compute (s, S) levels for a given cycle. Up to 99.8% of the search tree is pruned by a branch-and-bound technique with bounds generated by dynamic programming. A numerical study shows that the method can solve instances of realistic size in a reasonable time.

Published
2020
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21. Other malignancies in the history of CLL: an international multicenter study conducted by ERIC, the European Research Initiative on CLL, in HARMONY

Author

Chatzikonstantinou, Thomas, Scarfò, Lydia, Karakatsoulis, Georgios, Minga, Eva, Chamou, Dimitra, Iacoboni, Gloria, Kotaskova, Jana, Demosthenous, Christos, Smolej, Lukas, Mulligan, Stephen, Alcoceba, Miguel, Al-Shemari, Salem, Aurran-Schleinitz, Thérèse, Bacchiarri, Francesca, Bellido, Mar, Bijou, Fontanet, Calleja, Anne, Medina, Angeles, Khan, Mehreen Ali, Cassin, Ramona, Chatzileontiadou, Sofia, Collado, Rosa, Christian, Amy, Davis, Zadie, Dimou, Maria, Donaldson, David, Santos, Gimena Dos, Dreta, Barbara, Efstathopoulou, Maria, El-Ashwah, Shaimaa, Enrico, Alicia, Fresa, Alberto, Galimberti, Sara, Galitzia, Andrea, García-Serra, Rocío, Gimeno, Eva, González-Gascón-y-Marín, Isabel, Gozzetti, Alessandro, Guarente, Valerio, Guieze, Romain, Gogia, Ajay, Gupta, Ritu, Harrop, Sean, Hatzimichael, Eleftheria, Herishanu, Yair, Hernández-Rivas, José-Ángel, Inchiappa, Luca, Jaksic, Ozren, Janssen, Susanne, Kalicińska, Elżbieta, Laribi, Kamel, Karakus, Volkan, Kater, Arnon P., Kho, Bonnie, Kislova, Maria, Konstantinou, Eliana, Koren-Michowitz, Maya, Kotsianidis, Ioannis, Kreitman, Robert J., Labrador, Jorge, Lad, Deepesh, Levin, Mark-David, Levy, Ilana, Longval, Thomas, Lopez-Garcia, Alberto, Marquet, Juan, Martin-Rodríguez, Lucia, Maynadié, Marc, Maslejova, Stanislava, Mayor-Bastida, Carlota, Mihaljevic, Biljana, Milosevic, Ivana, Miras, Fatima, Moia, Riccardo, Morawska, Marta, Murru, Roberta, Nath, Uttam Kumar, Navarro-Bailón, Almudena, Oliveira, Ana C., Olivieri, Jacopo, Oscier, David, Panovska-Stavridis, Irina, Papaioannou, Maria, Papajík, Tomas, Kubova, Zuzana, Phumphukhieo, Punyarat, Pierie, Cheyenne, Puiggros, Anna, Rani, Lata, Reda, Gianluigi, Rigolin, Gian Matteo, Ruchlemer, Rosa, Daniel de Deus Santos, Marcos, Schipani, Mattia, Schiwitza, Annett, Shen, Yandong, Simkovic, Martin, Smirnova, Svetlana, Abdelrahman Soliman, Dina Sameh, Spacek, Martin, Tadmor, Tamar, Tomic, Kristina, Tse, Eric, Vassilakopoulos, Theodoros, Visentin, Andrea, Vitale, Candida, von Tresckow, Julia, Vrachiolias, George, Vukovic, Vojin, Walewska, Renata, Wasik-Szczepanek, Ewa, Xu, Zhenshu, Yagci, Munci, Yañez, Lucrecia, Yassin, Mohamed, Zuchnicka, Jana, Angelopoulou, Maria, Antic, Darko, Biderman, Bella, Catherwood, Mark, Claus, Rainer, Coscia, Marta, Cuneo, Antonio, Demirkan, Fatih, Espinet, Blanca, Gaidano, Gianluca, Kalashnikova, Olga B., Laurenti, Luca, Nikitin, Eugene, Pangalis, Gerassimos A., Panagiotidis, Panagiotis, Popov, Viola Maria, Pospisilova, Sarka, Sportoletti, Paolo, Stavroyianni, Niki, Tam, Constantine, Trentin, Livio, Chatzidimitriou, Anastasia, Bosch, Francesc, Doubek, Michael, Ghia, Paolo, and Stamatopoulos, Kostas

Published
2023
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23. Protein kinase CK2α is overexpressed in classical hodgkin lymphoma, regulates key signaling pathways, PD-L1 and may represent a new target for therapy

Author

Ruggeri, Edoardo, primary, Frezzato, Federica, additional, Mouawad, Nayla, additional, Pizzi, Marco, additional, Scarmozzino, Federico, additional, Capasso, Guido, additional, Trimarco, Valentina, additional, Quotti Tubi, Laura, additional, Cellini, Alessandro, additional, Cavarretta, Chiara Adele, additional, Ruocco, Valeria, additional, Serafin, Andrea, additional, Angotzi, Francesco, additional, Danesin, Nicolò, additional, Manni, Sabrina, additional, Facco, Monica, additional, Piazza, Francesco, additional, Trentin, Livio, additional, and Visentin, Andrea, additional

Published
2024
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24. A rescue approach in refractory diffuse large B-cell lymphoma with obinutuzumab-redirected cytokine-induced killer cells: a first-in-human case report

Author

Elice, Francesca, primary, Sommaggio, Roberta, additional, Cappuzzello, Elisa, additional, Riva, Marcello, additional, Tisi, Maria Chiara, additional, Bernardi, Martina, additional, Bozza, Angela, additional, Catanzaro, Daniela, additional, Chieregato, Katia, additional, Merlo, Anna, additional, Giaretta, Ilaria, additional, Pieta, Anna Dalla, additional, Krampera, Mauro, additional, Visco, Carlo, additional, Trentin, Livio, additional, Visentin, Andrea, additional, Tosetto, Alberto, additional, Astori, Giuseppe, additional, and Rosato, Antonio, additional

Published
2024
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25. Exploring the prognostic role of complex karyotype in chronic lymphocytic leukaemia patients treated with venetoclax‐based regimens

Author

Serafin, Andrea, primary, Cellini, Alessandro, additional, Cavarretta, Chiara Adele, additional, Ruocco, Valeria, additional, Angotzi, Francesco, additional, Zatta, Ivan, additional, Frezzato, Federica, additional, Bonaldi, Laura, additional, Martines, Annalisa, additional, Pravato, Stefano, additional, Piazza, Francesco, additional, Trentin, Livio, additional, and Visentin, Andrea, additional

Published
2024
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27. Efficacy and safety of venetoclax plus hypomethylating agents in relapsed/refractory acute myeloid leukemia: a multicenter real-life experience

Author

Angotzi, Francesco, primary, Lessi, Federica, additional, Leoncin, Matteo, additional, Filì, Carla, additional, Endri, Mauro, additional, Lico, Albana, additional, Visentin, Andrea, additional, Pravato, Stefano, additional, Candoni, Anna, additional, Trentin, Livio, additional, and Gurrieri, Carmela, additional

Published
2024
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28. When Waldenström macroglobulinemia hits the kidney: Description of a case series and management of a “rare in rare” scenario

Author

Danesin, Nicolò, primary, Scapinello, Greta, additional, Del Prete, Dorella, additional, Naso, Elena, additional, Berno, Tamara, additional, Visentin, Andrea, additional, Bonaldi, Laura, additional, Martines, Annalisa, additional, Bertorelle, Roberta, additional, Vianello, Fabrizio, additional, Gurrieri, Carmela, additional, Zambello, Renato, additional, Castellani, Chiara, additional, Fedrigo, Marny, additional, Rizzo, Stefania, additional, Angelini, Annalisa, additional, Trentin, Livio, additional, and Piazza, Francesco, additional

Published
2024
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31. Thrombotic and bleeding complications in patients with chronic lymphocytic leukemia and severe COVID-19: a study of ERIC, the European Research Initiative on CLL

Author

Antic, Darko, Milic, Natasa, Chatzikonstantinou, Thomas, Scarfò, Lydia, Otasevic, Vladimir, Rajovic, Nina, Allsup, David, Alonso Cabrero, Alejandro, Andres, Martin, Baile Gonzales, Monica, Capasso, Antonella, Collado, Rosa, Cordoba, Raul, Cuéllar-García, Carolina, Correa, Juan Gonzalo, De Paoli, Lorenzo, De Paolis, Maria Rosaria, Del Poeta, Giovanni, Dimou, Maria, Doubek, Michael, Efstathopoulou, Maria, El-Ashwah, Shaimaa, Enrico, Alicia, Espinet, Blanca, Farina, Lucia, Ferrari, Angela, Foglietta, Myriam, Lopez-Garcia, Alberto, García-Marco, José A., García-Serra, Rocío, Gentile, Massimo, Gimeno, Eva, da Silva, Maria Gomes, Gutwein, Odit, Hakobyan, Yervand K., Herishanu, Yair, Hernández-Rivas, José Ángel, Herold, Tobias, Itchaki, Gilad, Jaksic, Ozren, Janssens, Ann, Kalashnikova, Olga B., Kalicińska, Elżbieta, Kater, Arnon P., Kersting, Sabina, Koren-Michowitz, Maya, Labrador, Jorge, Lad, Deepesh, Laurenti, Luca, Fresa, Alberto, Levin, Mark-David, Mayor Bastida, Carlota, Malerba, Lara, Marasca, Roberto, Marchetti, Monia, Marquet, Juan, Mihaljevic, Biljana, Milosevic, Ivana, Mirás, Fatima, Morawska, Marta, Motta, Marina, Munir, Talha, Murru, Roberta, Nunes, Raquel, Olivieri, Jacopo, Pavlovsky, Miguel Arturo, Piskunova, Inga, Popov, Viola Maria, Quaglia, Francesca Maria, Quaresmini, Giulia, Reda, Gianluigi, Rigolin, Gian Matteo, Shrestha, Amit, Šimkovič, Martin, Smirnova, Svetlana, Špaček, Martin, Sportoletti, Paolo, Stanca, Oana, Stavroyianni, Niki, Te Raa, Doreen, Tomic, Kristina, Tonino, Sanne, Trentin, Livio, Van Der Spek, Ellen, van Gelder, Michel, Varettoni, Marzia, Visentin, Andrea, Vitale, Candida, Vukovic, Vojin, Wasik-Szczepanek, Ewa, Wróbel, Tomasz, Segundo, Lucrecia Yáñez San, Yassin, Mohamed, Coscia, Marta, Rambaldi, Alessandro, Montserrat, Emili, Foà, Robin, Cuneo, Antonio, Carrier, Marc, Ghia, Paolo, and Stamatopoulos, Kostas

Published
2022
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32. AI-Based Task Classification With Pressure Insoles for Occupational Safety

Author

O’Sullivan, Patricia, Menolotto, Matteo, Visentin, Andrea, O’Flynn, Brendan, Komaris, Dimitrios-Sokratis, O’Sullivan, Patricia, Menolotto, Matteo, Visentin, Andrea, O’Flynn, Brendan, and Komaris, Dimitrios-Sokratis

Abstract

Pressure insoles allow for the collection of real time pressure data inside and outside a laboratory setting as they are non-intrusive and can be simply integrated into industrial environments for occupational health and safety monitoring purposes. Activity detection is important for the safety and wellbeing of workers, and the present study aims to employ pressure insoles to detect the type of industry-related task an individual is performing by using random forest, an artificial intelligence-based classification technique. Twenty subjects wore loadsol® pressure insoles and performed five specific tasks associated with a typical workflow: standing, walking, pick and place, assembly, and manual handling. For each activity, statistical and morphological features were extracted to create a training dataset. The classifier performed with an accuracy of 82%, and a re-analysis focusing on the five most influential features resulted in 83% accuracy. These accuracies are comparable to similar task classification studies but with the benefit of added explainability, which increases transparency and, thereby, trust in the classifier decisions. The combination of random forest and in-depth feature analysis (SHAP) provided insights into the importance of certain features and the impact of their value on the classification of each task. The insights obtained from these methods can aid in the design of pressure insoles that are optimized for the extraction of impactful features and the prevention of work-related musculoskeletal disorders in Industry 4.0 operators.

Published
2024

33. Venetoclax infectious risk score to identify patients with chronic lymphocytic leukemia at high infectious risk during venetoclax treatment: A multicenter SEIFEM study

Author

Autore, Francesco, Visentin, Andrea, Deodato, Marina, Vitale, Candida, Galli, Eugenio, Fresa, Alberto, Fazzi, Rita, Sanna, Alessandro, Olivieri, Jacopo, Scortechini, Ilaria, Del Principe, Maria Ilaria, Sportoletti, Paolo, Schiattone, Luana, Maschio, Nilla, Facchinelli, Davide, Marchesi, Francesco, Coscia, Marta, Tedeschi, Alessandra, Trentin, Livio, Innocenti, Idanna, Candoni, Anna, Busca, Alessandro, Pagano, Livio, Laurenti, Luca, Pagano, Livio (ORCID:0000-0001-8287-928X), Laurenti, Luca (ORCID:0000-0002-8327-1396), Autore, Francesco, Visentin, Andrea, Deodato, Marina, Vitale, Candida, Galli, Eugenio, Fresa, Alberto, Fazzi, Rita, Sanna, Alessandro, Olivieri, Jacopo, Scortechini, Ilaria, Del Principe, Maria Ilaria, Sportoletti, Paolo, Schiattone, Luana, Maschio, Nilla, Facchinelli, Davide, Marchesi, Francesco, Coscia, Marta, Tedeschi, Alessandra, Trentin, Livio, Innocenti, Idanna, Candoni, Anna, Busca, Alessandro, Pagano, Livio, Laurenti, Luca, Pagano, Livio (ORCID:0000-0001-8287-928X), and Laurenti, Luca (ORCID:0000-0002-8327-1396)

Abstract

N/A

Published
2024

35. Baseline prognostic predictors in classical Hodgkin Lymphoma: a retrospective, single-center analysis on patients treated with PET/CT-guided ABVD.

Author

Cellini, Alessandro, Cavarretta, Chiara Adele, Angotzi, Francesco, Ruocco, Valeria, Serafin, Andrea, Danesin, Nicolò, Pizzi, Marco, Gregianin, Michele, Vio, Stefania, Crimì, Filippo, Vianello, Federica, Piazza, Francesco, Trentin, Livio, and Visentin, Andrea

Subjects
HODGKIN'S disease, PROGNOSIS, PROGNOSTIC models, SURVIVAL analysis (Biometry), LEUCOCYTOSIS, LYMPHOPENIA
Abstract

Introduction: The identification of baseline prognostic factors in Classical Hodgkin Lymphoma could help in tailoring a risk-based approach as the therapeutic landscape expands. Currently, the International Prognostic Score (IPS) represents the most used prediction tool in clinical practice, but other potential baseline risk predictors have been identified. Methods: We performed a retrospective analysis in a cohort of 274 patients treated with 18FDG-PET/CT-guided ABVD to assess the prognostic significance of the IPS risk factors, and to validate the impact of the peripheral blood lymphocyte to monocyte (LMR) and neutrophil to lymphocyte (NLR) ratios on prognosis definition. Results: Among the considered risk factors, stage IV disease (HR 1.83), leukocytosis (HR 2.28), anemia (HR 3.23) and low LMR (HR 2.01) significantly predicted PFS, whereas male sex (HR 2.93), stage IV disease (HR 3.00) and lymphopenia (HR 7.84) significantly predicted OS. A 4 variable and a 3 variable prognostic system was subsequently proposed for PFS and OS, respectively. In both cases, a stark decrease in the survival probability was documented as the score increased. Moreover, by selecting only the significant IPS items and considering a more recently proposed prognostic factor (LMR) we were able to better identify patients at higher risk of relapsing after PET/CT-guided ABVD. Discussion: Although the IPS was still able to identify a subgroup of high-risk patients within our cohort of individuals treated with PET/CT-guided ABVD, not all the risk factors that it considers were found to have an impact on survival times. Moreover, by selecting only the significant IPS items and considering a more recently proposed prognostic factor (LMR) we were able to better identify patients at higher risk of relapse, in an effort to contribute to the building of a modern risk prediction tool that can help guide treatment choices. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Focal adhesion kinase as a new player in the biology of oncohematological diseases: the starting evidence.

Author

Capasso, Guido, Mouawad, Nayla, Castronuovo, Maria, Ruggeri, Edoardo, Visentin, Andrea, Trentin, Livio, and Frezzato, Federica

Subjects
FOCAL adhesion kinase, EXTRACELLULAR matrix, FOCAL adhesions, PROTEIN-tyrosine kinases, EPITHELIAL-mesenchymal transition
Abstract

Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase mainly found in the focal adhesion regions of the plasma membrane and it has a crucial role in migration and the remodeling of cellular morphology. FAK is also linked to several aspects of cancer biology, from cytokine production to angiogenesis, drug resistance, invasion, and metastasis, as well as epithelial-to-mesenchymal transition. The gene locus of FAK is frequently amplified in several human tumors, thus causing FAK overexpression in several cancers. Furthermore, FAK can influence extracellular matrix production and exosome secretion through cancer-associated fibroblasts, thus it has an important role in tumor microenvironment regulation. Although the role of FAK in solid tumors is well known, its importance in onco-hematological diseases remains poorly explored. This review collects studies related to FAK significance in onco-hematological diseases and their microenvironments. Overall, the importance of FAK in blood tumors is increasingly evident, but further research is required to confirm it as a new therapeutic target in hematological contexts. [ABSTRACT FROM AUTHOR]

Published
2024
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37. CD49d expression is included in a revised 4‐factor model predicting outcome in patients with chronic lymphocytic leukemia treated with ibrutinib: A multicenter real‐world experience.

Author

Bomben, Riccardo, Zucchetto, Antonella, Laureana, Roberta, Chiarenza, Annalisa, Olivieri, Jacopo, Tissino, Erika, Rossi, Francesca M., Vit, Filippo, Bittolo, Tamara, Papotti, Robel, Pozzo, Federico, Gaglio, Annalisa, Degan, Massimo, Polesel, Jerry, Marasca, Roberto, Visentin, Andrea, Moia, Riccardo, Innocenti, Idanna, Vitale, Candida, and Murru, Roberta

Published
2024
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38. COVID-19 severity and mortality in patients with CLL: an update of the international ERIC and Campus CLL study

Author

Chatzikonstantinou, Thomas, Kapetanakis, Anargyros, Scarfò, Lydia, Karakatsoulis, Georgios, Allsup, David, Cabrero, Alejandro Alonso, Andres, Martin, Antic, Darko, Baile, Mónica, Baliakas, Panagiotis, Bron, Dominique, Capasso, Antonella, Chatzileontiadou, Sofia, Cordoba, Raul, Correa, Juan-Gonzalo, Cuéllar-García, Carolina, De Paoli, Lorenzo, De Paolis, Maria Rosaria, Del Poeta, Giovanni, Demosthenous, Christos, Dimou, Maria, Donaldson, David, Doubek, Michael, Efstathopoulou, Maria, Eichhorst, Barbara, El-Ashwah, Shaimaa, Enrico, Alicia, Espinet, Blanca, Farina, Lucia, Ferrari, Angela, Foglietta, Myriam, Frederiksen, Henrik, Fürstenau, Moritz, García-Marco, José A., García-Serra, Rocío, Gentile, Massimo, Gimeno, Eva, Glenthøj, Andreas, Gomes da Silva, Maria, Gutwein, Odit, Hakobyan, Yervand K., Herishanu, Yair, Hernández-Rivas, José Ángel, Herold, Tobias, Innocenti, Idanna, Itchaki, Gilad, Jaksic, Ozren, Janssens, Ann, Kalashnikova, Оlga B., Kalicińska, Elżbieta, Karlsson, Linda Katharina, Kater, Arnon P., Kersting, Sabina, Labrador, Jorge, Lad, Deepesh, Laurenti, Luca, Levin, Mark-David, Lista, Enrico, Lopez-Garcia, Alberto, Malerba, Lara, Marasca, Roberto, Marchetti, Monia, Marquet, Juan, Mattsson, Mattias, Mauro, Francesca R., Milosevic, Ivana, Mirás, Fatima, Morawska, Marta, Motta, Marina, Munir, Talha, Murru, Roberta, Niemann, Carsten U., Rodrigues, Raquel Nunes, Olivieri, Jacopo, Orsucci, Lorella, Papaioannou, Maria, Pavlovsky, Miguel Arturo, Piskunova, Inga, Popov, Viola Maria, Quaglia, Francesca Maria, Quaresmini, Giulia, Qvist, Kristian, Reda, Gianluigi, Rigolin, Gian Matteo, Ruchlemer, Rosa, Saghumyan, Gevorg, Shrestha, Amit, Šimkovič, Martin, Špaček, Martin, Sportoletti, Paolo, Stanca, Oana, Stavroyianni, Niki, Tadmor, Tamar, Te Raa, Doreen, Tonino, Sanne H., Trentin, Livio, Van Der Spek, Ellen, van Gelder, Michel, van Kampen, Roel, Varettoni, Marzia, Visentin, Andrea, Vitale, Candida, Wasik-Szczepanek, Ewa, Wróbel, Tomasz, San Segundo, Lucrecia Yáñez, Yassin, Mohamed, Coscia, Marta, Rambaldi, Alessandro, Montserrat, Emili, Foà, Robin, Cuneo, Antonio, Stamatopoulos, Kostas, and Ghia, Paolo

Published
2021
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40. Long-term follow-up of cladribine treatment in hairy cell leukemia: 30-year experience in a multicentric Italian study

Author

Pagano, Livio, Criscuolo, Marianna, Broccoli, Alessandro, Piciocchi, Alfonso, Varettoni, Marzia, Galli, Eugenio, Anastasia, Antonella, Cantonetti, Maria, Trentin, Livio, Kovalchuk, Sofia, Orsucci, Lorella, Frustaci, Annamaria, Spolzino, Angelica, Volpetti, Stefano, Annibali, Ombretta, Storti, Sergio, Stelitano, Caterina, Marchesi, Francesco, Offidani, Massimo, Casadei, Beatrice, Nizzoli, Maria Elena, De Luca, Maria Lucia, Fianchi, Luana, Motta, Marina, Guarnera, Luca, Simonetti, Edoardo, Visentin, Andrea, Vassallo, Francesco, Deodato, Marina, Sarlo, Chiara, Olivieri, Attilio, Falini, Brunangelo, Pulsoni, Alessandro, Tiacci, Enrico, and Zinzani, Pier Luigi

Published
2022
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41. Financing gap for universal social protection: Global, regional and national estimates and strategies for creating fiscal space.

Author

Cattaneo, Umberto, Schwarzer, Helmut, Razavi, Shahra, and Visentin, Andrea

Subjects
SOCIAL security, GROSS domestic product, PUBLIC spending, LOW-income countries, MIDDLE-income countries
Abstract

The primary aim of the study is to provide updated estimates of the financing gap to attain universal coverage for social protection floors. This estimation encompasses 133 low- and middle-income countries, and includes five income security guarantees (for children, persons with severe disabilities, mothers of newborns, older persons and the unemployed), together with essential health care. Estimates show that, for low- and middle-income countries, the financing gap to achieve universal coverage of social protection floors is 3.3 per cent of GDP annually.1 However, for low-income countries, the financing gap is an overwhelming 52.3 per cent of their GDP annually. In 2024, for low- and middle-income countries, the additional government spending needed to achieve universal social protection represents 10.6 per cent of their annual government expenditure, or 31.6 per cent of their social protection expenditure. However, for low-income countries, building social protection floors requires the mobilization of four times their annual government expenditure or nearly 28 times their social protection expenditure. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Impact of the presence and number of chromosomal abnormalities on the clinical outcome in Waldenström Macroglobulinemia: a monocentric experience

Author

Danesin, Nicolò, primary, Bonaldi, Laura, additional, Martines, Annalisa, additional, Nalio, Silvia, additional, Bertorelle, Roberta, additional, Compagno, Sofia, additional, Marcato, Raffaella, additional, Manni, Sabrina, additional, Scarmozzino, Federico, additional, Pizzi, Marco, additional, Tos, Angelo Paolo Dei, additional, Cellini, Alessandro, additional, Scapinello, Greta, additional, Visentin, Andrea, additional, Trentin, Livio, additional, and Piazza, Francesco, additional

Published
2024
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45. p66Shc deficiency in CLL cells enhances PD-L1 expression and suppresses immune synapse formation

Author

Lopresti, Ludovica, primary, Capitani, Nagaja, additional, Tatangelo, Vanessa, additional, Tangredi, Carmela, additional, Boncompagni, Gioia, additional, Frezzato, Federica, additional, Visentin, Andrea, additional, Marotta, Giuseppe, additional, Ciofini, Sara, additional, Gozzetti, Alessandro, additional, Bocchia, Monica, additional, Trentin, Livio, additional, Baldari, Cosima T., additional, and Patrussi, Laura, additional

Published
2024
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47. Ibrutinib as first line therapy in chronic lymphocytic leukemia patients over 80 years old: A retrospective real‐life multicenter Italian cohort

Author

Martino, Enrica Antonia, primary, Mauro, Francesca Romana, additional, Reda, Gianluigi, additional, Laurenti, Luca, additional, Visentin, Andrea, additional, Frustaci, Annamaria, additional, Vigna, Ernesto, additional, Pepe, Sara, additional, Catania, Gioacchino, additional, Loseto, Giacomo, additional, Murru, Roberta, additional, Chiarenza, Annalisa, additional, Sportoletti, Paolo, additional, Del Principe, Maria Ilaria, additional, Laureana, Roberta, additional, Coscia, Marta, additional, Galimberti, Sara, additional, Ferretti, Eleonora, additional, Zucchetto, Antonella, additional, Bomben, Riccardo, additional, Polesel, Jerry, additional, Tedeschi, Alessandra, additional, Rossi, Davide, additional, Trentin, Livio, additional, Neri, Antonino, additional, Morabito, Fortunato, additional, Gattei, Valter, additional, and Gentile, Massimo, additional

Published
2024
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50. Modelling Dynamic Programming-Based Global Constraints in Constraint Programming

Author

Visentin, Andrea, Prestwich, Steven D., Rossi, Roberto, Tarim, Armagan, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Le Thi, Hoai An, editor, Le, Hoai Minh, editor, and Pham Dinh, Tao, editor

Published
2020
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