15,573 results on '"Marone A"'
Search Results
2. Material synthesis through simulations guided by machine learning: a position paper
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Syed, Usman, Cunico, Federico, Khan, Uzair, Radicchi, Eros, Setti, Francesco, Speghini, Adolfo, Marone, Paolo, Semenzin, Filiberto, and Cristani, Marco
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Computer Science - Machine Learning - Abstract
In this position paper, we propose an approach for sustainable data collection in the field of optimal mix design for marble sludge reuse. Marble sludge, a calcium-rich residual from stone-cutting processes, can be repurposed by mixing it with various ingredients. However, determining the optimal mix design is challenging due to the variability in sludge composition and the costly, time-consuming nature of experimental data collection. Also, we investigate the possibility of using machine learning models using meta-learning as an optimization tool to estimate the correct quantity of stone-cutting sludge to be used in aggregates to obtain a mix design with specific mechanical properties that can be used successfully in the building industry. Our approach offers two key advantages: (i) through simulations, a large dataset can be generated, saving time and money during the data collection phase, and (ii) Utilizing machine learning models, with performance enhancement through hyper-parameter optimization via meta-learning, to estimate optimal mix designs reducing the need for extensive manual experimentation, lowering costs, minimizing environmental impact, and accelerating the processing of quarry sludge. Our idea promises to streamline the marble sludge reuse process by leveraging collective data and advanced machine learning, promoting sustainability and efficiency in the stonecutting sector.
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- 2024
3. SeisLM: a Foundation Model for Seismic Waveforms
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Liu, Tianlin, Münchmeyer, Jannes, Laurenti, Laura, Marone, Chris, de Hoop, Maarten V., and Dokmanić, Ivan
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Physics - Geophysics ,Computer Science - Machine Learning - Abstract
We introduce the Seismic Language Model (SeisLM), a foundational model designed to analyze seismic waveforms -- signals generated by Earth's vibrations such as the ones originating from earthquakes. SeisLM is pretrained on a large collection of open-source seismic datasets using a self-supervised contrastive loss, akin to BERT in language modeling. This approach allows the model to learn general seismic waveform patterns from unlabeled data without being tied to specific downstream tasks. When fine-tuned, SeisLM excels in seismological tasks like event detection, phase-picking, onset time regression, and foreshock-aftershock classification. The code has been made publicly available on https://github.com/liutianlin0121/seisLM.
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- 2024
4. A universal reconstruction method for X ray scattering tensor tomography based on wavefront modulation
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Lautizi, Ginevra, Studer, Alain, Zdora, Marie-Christine, De Marco, Fabio, Kim, Jisoo, Di Trapani, Vittorio, Marone, Federica, Thibault, Pierre, and Stampanoni, Marco
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Physics - Applied Physics ,Physics - Medical Physics - Abstract
We present a versatile method for full-field, X-ray scattering tensor tomography that is based on energy conservation and is applicable to data obtained using different wavefront modulators. Using this algorithm, we pave the way for speckle-based tensor tomography. The proposed model relies on a mathematical approach that allows tuning spatial resolution and signal sensitivity. We present the application of the algorithm to three different imaging modalities and demonstrate its potential for applications of X-ray directional dark-field imaging., Comment: Accepted by Physical Review Applied
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- 2024
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5. Root growth and biomass partitioning of nine juvenile Sahelian agroforestry tree species under drought and irrigation treatments
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Gning, Fatou, Jourdan, Christophe, Marone, Diatta, Ngom, Daouda, and Ræbild, Anders
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- 2025
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6. Structural variation in the pangenome of wild and domesticated barley
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Jayakodi, Murukarthick, Lu, Qiongxian, Pidon, Hélène, Rabanus-Wallace, M. Timothy, Bayer, Micha, Lux, Thomas, Guo, Yu, Jaegle, Benjamin, Badea, Ana, Bekele, Wubishet, Brar, Gurcharn S., Braune, Katarzyna, Bunk, Boyke, Chalmers, Kenneth J., Chapman, Brett, Jørgensen, Morten Egevang, Feng, Jia-Wu, Feser, Manuel, Fiebig, Anne, Gundlach, Heidrun, Guo, Wenbin, Haberer, Georg, Hansson, Mats, Himmelbach, Axel, Hoffie, Iris, Hoffie, Robert E., Hu, Haifei, Isobe, Sachiko, König, Patrick, Kale, Sandip M., Kamal, Nadia, Keeble-Gagnère, Gabriel, Keller, Beat, Knauft, Manuela, Koppolu, Ravi, Krattinger, Simon G., Kumlehn, Jochen, Langridge, Peter, Li, Chengdao, Marone, Marina P., Maurer, Andreas, Mayer, Klaus F. X., Melzer, Michael, Muehlbauer, Gary J., Murozuka, Emiko, Padmarasu, Sudharsan, Perovic, Dragan, Pillen, Klaus, Pin, Pierre A., Pozniak, Curtis J., Ramsay, Luke, Pedas, Pai Rosager, Rutten, Twan, Sakuma, Shun, Sato, Kazuhiro, Schüler, Danuta, Schmutzer, Thomas, Scholz, Uwe, Schreiber, Miriam, Shirasawa, Kenta, Simpson, Craig, Skadhauge, Birgitte, Spannagl, Manuel, Steffenson, Brian J., Thomsen, Hanne C., Tibbits, Josquin F., Nielsen, Martin Toft Simmelsgaard, Trautewig, Corinna, Vequaud, Dominique, Voss, Cynthia, Wang, Penghao, Waugh, Robbie, Westcott, Sharon, Rasmussen, Magnus Wohlfahrt, Zhang, Runxuan, Zhang, Xiao-Qi, Wicker, Thomas, Dockter, Christoph, Mascher, Martin, and Stein, Nils
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- 2024
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7. AdapterSwap: Continuous Training of LLMs with Data Removal and Access-Control Guarantees
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Fleshman, William, Khan, Aleem, Marone, Marc, and Van Durme, Benjamin
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
Large language models (LLMs) are increasingly capable of completing knowledge intensive tasks by recalling information from a static pretraining corpus. Here we are concerned with LLMs in the context of evolving data requirements. For instance: batches of new data that are introduced periodically; subsets of data with user-based access controls; or requirements on dynamic removal of documents with guarantees that associated knowledge cannot be recalled. We wish to satisfy these requirements while at the same time ensuring a model does not forget old information when new data becomes available. To address these issues, we introduce AdapterSwap, a training and inference scheme that organizes knowledge from a data collection into a set of low-rank adapters, which are dynamically composed during inference. Our experiments demonstrate AdapterSwap's ability to support efficient continual learning, while also enabling organizations to have fine-grained control over data access and deletion.
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- 2024
8. Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data
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Zhang, Jingyu, Marone, Marc, Li, Tianjian, Van Durme, Benjamin, and Khashabi, Daniel
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Computer Science - Computation and Language - Abstract
To trust the fluent generations of large language models (LLMs), humans must be able to verify their correctness against trusted, external sources. Recent efforts, such as providing citations via retrieved documents or post-hoc provenance, enhance verifiability but provide no guarantees on their correctness. To address these limitations, we tackle the verifiability goal with a different philosophy: trivializing the verification process by developing models that quote verbatim statements from trusted sources in their pre-training data. We propose Quote-Tuning, which demonstrates the feasibility of aligning models to quote. The core of Quote-Tuning is a fast membership inference function that efficiently verifies text against trusted corpora. We leverage this tool to design a reward function to quantify quotes in model responses, and curate datasets for preference learning. Experiments show that Quote-Tuning significantly increases verbatim quotes from high-quality documents by up to 130% relative to base models while maintaining response quality. Quote-Tuning is applicable in different tasks, generalizes to out-of-domain data and diverse model families, and provides additional benefits to truthfulness. Our method not only serves as a hassle-free method to increase quoting but also opens up avenues for improving LLM trustworthiness through better verifiability.
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- 2024
9. Dated Data: Tracing Knowledge Cutoffs in Large Language Models
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Cheng, Jeffrey, Marone, Marc, Weller, Orion, Lawrie, Dawn, Khashabi, Daniel, and Van Durme, Benjamin
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Computer Science - Computation and Language - Abstract
Released Large Language Models (LLMs) are often paired with a claimed knowledge cutoff date, or the dates at which training data was gathered. Such information is crucial for applications where the LLM must provide up to date information. However, this statement only scratches the surface: do all resources in the training data share the same knowledge cutoff date? Does the model's demonstrated knowledge for these subsets closely align to their cutoff dates? In this work, we define the notion of an effective cutoff. This is distinct from the LLM designer reported cutoff and applies separately to sub-resources and topics. We propose a simple approach to estimate effective cutoffs on the resource-level temporal alignment of an LLM by probing across versions of the data. Using this analysis, we find that effective cutoffs often differ from reported cutoffs. To understand the root cause of this observation, we conduct a direct large-scale analysis on open pre-training datasets. Our analysis reveals two reasons for these inconsistencies: (1) temporal biases of CommonCrawl data due to non-trivial amounts of old data in new dumps and (2) complications in LLM deduplication schemes involving semantic duplicates and lexical near-duplicates. Overall, our results show that knowledge cutoffs are not as simple as they have seemed and that care must be taken both by LLM dataset curators as well as practitioners who seek to use information from these models.
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- 2024
10. Energy dissipation in earthquakes
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Kammer, David S., McLaskey, Gregory C., Abercrombie, Rachel E., Ampuero, Jean-Paul, Cattania, Camilla, Cocco, Massimo, Zilio, Luca Dal, Dresen, Georg, Gabriel, Alice-Agnes, Ke, Chun-Yu, Marone, Chris, Selvadurai, Paul A., and Tinti, Elisa
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Physics - Geophysics - Abstract
Earthquakes are rupture-like processes that propagate along tectonic faults and cause seismic waves. The propagation speed and final area of the rupture, which determine an earthquake's potential impact, are directly related to the nature and quantity of the energy dissipation involved in the rupture process. Here we present the challenges associated with defining and measuring the energy dissipation in laboratory and natural earthquakes across many scales. We discuss the importance and implications of distinguishing between energy dissipation that occurs close to and far behind the rupture tip and we identify open scientific questions related to a consistent modeling framework for earthquake physics that extends beyond classical Linear Elastic Fracture Mechanics., Comment: 8 pages, 2 figures
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- 2024
11. StarCoder 2 and The Stack v2: The Next Generation
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Lozhkov, Anton, Li, Raymond, Allal, Loubna Ben, Cassano, Federico, Lamy-Poirier, Joel, Tazi, Nouamane, Tang, Ao, Pykhtar, Dmytro, Liu, Jiawei, Wei, Yuxiang, Liu, Tianyang, Tian, Max, Kocetkov, Denis, Zucker, Arthur, Belkada, Younes, Wang, Zijian, Liu, Qian, Abulkhanov, Dmitry, Paul, Indraneil, Li, Zhuang, Li, Wen-Ding, Risdal, Megan, Li, Jia, Zhu, Jian, Zhuo, Terry Yue, Zheltonozhskii, Evgenii, Dade, Nii Osae Osae, Yu, Wenhao, Krauß, Lucas, Jain, Naman, Su, Yixuan, He, Xuanli, Dey, Manan, Abati, Edoardo, Chai, Yekun, Muennighoff, Niklas, Tang, Xiangru, Oblokulov, Muhtasham, Akiki, Christopher, Marone, Marc, Mou, Chenghao, Mishra, Mayank, Gu, Alex, Hui, Binyuan, Dao, Tri, Zebaze, Armel, Dehaene, Olivier, Patry, Nicolas, Xu, Canwen, McAuley, Julian, Hu, Han, Scholak, Torsten, Paquet, Sebastien, Robinson, Jennifer, Anderson, Carolyn Jane, Chapados, Nicolas, Patwary, Mostofa, Tajbakhsh, Nima, Jernite, Yacine, Ferrandis, Carlos Muñoz, Zhang, Lingming, Hughes, Sean, Wolf, Thomas, Guha, Arjun, von Werra, Leandro, and de Vries, Harm
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Computer Science - Software Engineering ,Computer Science - Artificial Intelligence - Abstract
The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership with Software Heritage (SWH), we build The Stack v2 on top of the digital commons of their source code archive. Alongside the SWH repositories spanning 619 programming languages, we carefully select other high-quality data sources, such as GitHub pull requests, Kaggle notebooks, and code documentation. This results in a training set that is 4x larger than the first StarCoder dataset. We train StarCoder2 models with 3B, 7B, and 15B parameters on 3.3 to 4.3 trillion tokens and thoroughly evaluate them on a comprehensive set of Code LLM benchmarks. We find that our small model, StarCoder2-3B, outperforms other Code LLMs of similar size on most benchmarks, and also outperforms StarCoderBase-15B. Our large model, StarCoder2- 15B, significantly outperforms other models of comparable size. In addition, it matches or outperforms CodeLlama-34B, a model more than twice its size. Although DeepSeekCoder- 33B is the best-performing model at code completion for high-resource languages, we find that StarCoder2-15B outperforms it on math and code reasoning benchmarks, as well as several low-resource languages. We make the model weights available under an OpenRAIL license and ensure full transparency regarding the training data by releasing the SoftWare Heritage persistent IDentifiers (SWHIDs) of the source code data.
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- 2024
12. Probing the evolution of fault properties during the seismic cycle with deep learning
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Laurenti, Laura, Paoletti, Gabriele, Tinti, Elisa, Galasso, Fabio, Collettini, Cristiano, and Marone, Chris
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- 2024
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13. Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments
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Borate, Prabhav, Rivière, Jacques, Marty, Samson, Marone, Chris, Kifer, Daniel, and Shokouhi, Parisa
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- 2024
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14. Waste From Alwar Quartzite (A Global Heritage Stone From Rajasthan - India) As Secondary Raw Materials for Cementitious Tile Adhesives
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Graziano, Sossio Fabio, Marone, Paolo, Trinchillo, Antonio, Di Benedetto, Claudia, Montesano, Giovanna, Rispoli, Concetta, and Cappelletti, Piergiulio
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- 2024
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15. Role of critical stress in quantifying the magnitude of fluid-injection triggered earthquakes
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Yu, Jiayi, Eijsink, Agathe, Marone, Chris, Rivière, Jacques, Shokouhi, Parisa, and Elsworth, Derek
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- 2024
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16. Adapting malaria indicator surveys to investigate treatment adherence: a pilot study on Bioko Island, Equatorial Guinea
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Galick, David S., Donfack, Olivier Tresor, Mifumu, Teresa Ayingono Ondo, Onvogo, Cristina Ngui Otogo, Dougan, Teobaldo Babo, Mikue, Monica Idelvina Aling Ayen, Nguema, Godino Esono, Eribo, Charity Okoro, Euka, Maria Mirella Buila, Marone Martin, Kate P., Phiri, Wonder P., Guerra, Carlos A., and García, Guillermo A.
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- 2024
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17. Mediation role of interpersonal problems between insecure attachment and eating disorder psychopathology
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Carfagno, Marco, Barone, Eugenia, Arsenio, Eleonora, Bello, Rosaria, Marone, Luigi, Volpicelli, Antonio, Cascino, Giammarco, and Monteleone, Alessio Maria
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- 2024
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18. Author Correction: Earthquake energy dissipation in a fracture mechanics framework
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Kammer, David S., McLaskey, Gregory C., Abercrombie, Rachel E., Ampuero, Jean-Paul, Cattania, Camilla, Cocco, Massimo, Dal Zilio, Luca, Dresen, Georg, Gabriel, Alice-Agnes, Ke, Chun-Yu, Marone, Chris, Selvadurai, Paul Antony, and Tinti, Elisa
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- 2024
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19. Earthquake energy dissipation in a fracture mechanics framework
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Kammer, David S., McLaskey, Gregory C., Abercrombie, Rachel E., Ampuero, Jean-Paul, Cattania, Camilla, Cocco, Massimo, Dal Zilio, Luca, Dresen, Georg, Gabriel, Alice-Agnes, Ke, Chun-Yu, Marone, Chris, Selvadurai, Paul Antony, and Tinti, Elisa
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- 2024
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20. X-ray scattering tensor tomography based finite element modelling of heterogeneous materials
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Auenhammer, Robert M., Kim, Jisoo, Oddy, Carolyn, Mikkelsen, Lars P., Marone, Federica, Stampanoni, Marco, and Asp, Leif E.
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- 2024
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21. Crustal permeability generated through microearthquakes is constrained by seismic moment
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Yu, Pengliang, Mali, Ankur, Velaga, Thejasvi, Bi, Alex, Yu, Jiayi, Marone, Chris, Shokouhi, Parisa, and Elsworth, Derek
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- 2024
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22. Selective haematological cancer eradication with preserved haematopoiesis
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Garaudé, Simon, Marone, Romina, Lepore, Rosalba, Devaux, Anna, Beerlage, Astrid, Seyres, Denis, Dell’ Aglio, Alessandro, Juskevicius, Darius, Zuin, Jessica, Burgold, Thomas, Wang, Sisi, Katta, Varun, Manquen, Garret, Li, Yichao, Larrue, Clément, Camus, Anna, Durzynska, Izabela, Wellinger, Lisa C., Kirby, Ian, Van Berkel, Patrick H., Kunz, Christian, Tamburini, Jérôme, Bertoni, Francesco, Widmer, Corinne C., Tsai, Shengdar Q., Simonetta, Federico, Urlinger, Stefanie, and Jeker, Lukas T.
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- 2024
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23. High-Rate Phase Association with Travel Time Neural Fields
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Shi, Cheng, Poggiali, Giulio, Marone, Chris, de Hoop, Maarten V., and Dokmanić, Ivan
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Physics - Geophysics ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Earthquake science and seismology rely on the ability to associate seismic waves with their originating earthquakes. Earthquake detection algorithms based on deep learning have progressed rapidly and now routinely detect microearthquakes with unprecedented clarity, providing information about fault dynamics on increasingly finer spatiotemporal scales. However, this densification of detections can overwhelm existing techniques for phase association which rely on fixed wave speed models and associate events one by one. These methods fail when the event rates become high or where the 4D complexity of elastic wave speeds cannot be ignored. Here, we introduce HARPA, a deep learning solution to this problem. HARPA is a high-rate association framework which incorporates wave physics by leveraging deep generative models and travel time neural fields. Instead of associating events one by one, it lifts arrival sequences to probability distributions and compares them using an optimal transport metric. The generative travel time neural fields are used to estimate the wave speed simultaneously with association. HARPA outperforms state-of-the-art association methods for both real seismic data and complex synthetic models and paves the way for improved understanding of seismicity while establishing a new seismic data analysis paradigm.
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- 2023
24. Using in-situ strain measurements to evaluate the accuracy of stress estimation procedures from fracture injection/shut-in tests
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Guglielmi, Yves, McClure, Mark, Burghardt, Jeffrey, Morris, Joseph P, Doe, Thomas, Fu, Pengcheng, Knox, Hunter, Vermeul, Vince, Kneafsey, Tim, Team, The EGS Collab, Ajo-Franklin, J, Baumgartner, T, Beckers, K, Blankenship, D, Bonneville, A, Boyd, L, Brown, S, Burghardt, JA, Chai, C, Chakravarty, A, Chen, T, Chen, Y, Chi, B, Condon, K, Cook, PJ, Crandall, D, Dobson, PF, Doe, T, Doughty, CA, Elsworth, D, Feldman, J, Feng, Z, Foris, A, Frash, LP, Frone, Z, Fu, P, Gao, K, Ghassemi, A, Guglielmi, Y, Haimson, B, Hawkins, A, Heise, J, Hopp, C, Horn, M, Horne, RN, Horner, J, Hu, M, Huang, H, Huang, L, Im, KJ, Ingraham, M, Jafarov, E, Jayne, RS, Johnson, TC, Johnson, SE, Johnston, B, Karra, S, Kim, K, King, DK, Kneafsey, T, Knox, H, Knox, J, Kumar, D, Kutun, K, Lee, M, Li, D, Li, J, Li, K, Li, Z, Maceira, M, Mackey, P, Makedonska, N, Marone, CJ, Mattson, E, McClure, MW, McLennan, J, McLing, T, Medler, C, Mellors, RJ, Metcalfe, E, Miskimins, J, Moore, J, Morency, CE, Morris, JP, Myers, T, Nakagawa, S, Neupane, G, Newman, G, Nieto, A, Paronish, T, Pawar, R, Petrov, P, Pietzyk, B, Podgorney, R, Polsky, Y, Pope, J, Porse, S, Primo, JC, Pyatina, T, and Reimers, C
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Engineering ,Resources Engineering and Extractive Metallurgy ,Bioengineering ,DFIT ,Minifrac ,SIMFIP ,Collab ,Civil Engineering ,Mining & Metallurgy ,Civil engineering ,Resources engineering and extractive metallurgy - Abstract
Fracture injection/shut-in tests are commonly used to measure the state of stress in the subsurface. Injection creates a hydraulic fracture (or in some cases, opens a preexisting fracture), and then the pressure after shut-in is monitored to identify fracture closure. Different interpretation procedures have been proposed for estimating closure, and the procedures sometimes yield significantly different results. In this study, direct, in-situ strain measurements are used to observe fracture reopening and closure. The tests were performed as part of the EGS Collab project, a mesoscale project performed at 1.25 and 1.5 km depth at the Sanford Underground Research Facility. The tests were instrumented with the SIMFIP tool, a double-packer probe with a high-resolution three-dimensional borehole displacement sensor. The measurements provide a direct observation of the fracture closure signature, enabling a high-fidelity estimate of the fracture closure stress (ie, the normal stress on the fracture). In two of the four tests, injection created an opening mode fracture, and so the closure stress can be interpreted as the minimum principal stress. In the other two tests, injection probably opened preexisting natural fractures, and so the closure stress can be interpreted as the normal stress on the fractures. The strain measurements are compared against different proposed methods for estimating closure stress from pressure transients. The shut-in transients are analyzed with two techniques that are widely used in the field of petroleum engineering – the ‘tangent’ method and the ‘compliance’ method. In three of the four tests, the tangent method significantly underestimates the closure stress. The compliance method is reasonably accurate in all four tests. Closure stress is also interpreted using two other commonly-used methods – ‘first deviation from linearity’ and the method of (Hayashi and Haimson, 1991). In comparison with the SIMFIP data, these methods tend to overestimate the closure stress, evidently because they identify closure from early-time transient effects, such as near-wellbore tortuosity. In two of the tests, microseismic imaging provides an independent estimate of the size of the fracture created by injection. When combined with a simple mass balance calculation, the SIMFIP stress measurements yield predictions of fracture size that are reasonably consistent with the estimates from microseismic. The calculations imply an apparent fracture toughness 2-3x higher than typical laboratory-derived values.
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- 2023
25. 'According to ...': Prompting Language Models Improves Quoting from Pre-Training Data
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Weller, Orion, Marone, Marc, Weir, Nathaniel, Lawrie, Dawn, Khashabi, Daniel, and Van Durme, Benjamin
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence - Abstract
Large Language Models (LLMs) may hallucinate and generate fake information, despite pre-training on factual data. Inspired by the journalistic device of "according to sources", we propose according-to prompting: directing LLMs to ground responses against previously observed text. To quantify this grounding, we propose a novel evaluation metric (QUIP-Score) that measures the extent to which model-produced answers are directly found in underlying text corpora. We illustrate with experiments on three corpora (Wikipedia, PubMed, and the U.S. legal tax code) that these prompts improve grounding under our metrics, with the additional benefit of often improving end-task performance. Furthermore, prompts that ask the model to decrease grounding (or to ground to other corpora) indeed decrease QUIP-Score, indicating the ability of LLMs to increase or decrease grounded generations on request., Comment: Accepted to EACL 2024
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- 2023
26. StarCoder: may the source be with you!
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Li, Raymond, Allal, Loubna Ben, Zi, Yangtian, Muennighoff, Niklas, Kocetkov, Denis, Mou, Chenghao, Marone, Marc, Akiki, Christopher, Li, Jia, Chim, Jenny, Liu, Qian, Zheltonozhskii, Evgenii, Zhuo, Terry Yue, Wang, Thomas, Dehaene, Olivier, Davaadorj, Mishig, Lamy-Poirier, Joel, Monteiro, João, Shliazhko, Oleh, Gontier, Nicolas, Meade, Nicholas, Zebaze, Armel, Yee, Ming-Ho, Umapathi, Logesh Kumar, Zhu, Jian, Lipkin, Benjamin, Oblokulov, Muhtasham, Wang, Zhiruo, Murthy, Rudra, Stillerman, Jason, Patel, Siva Sankalp, Abulkhanov, Dmitry, Zocca, Marco, Dey, Manan, Zhang, Zhihan, Fahmy, Nour, Bhattacharyya, Urvashi, Yu, Wenhao, Singh, Swayam, Luccioni, Sasha, Villegas, Paulo, Kunakov, Maxim, Zhdanov, Fedor, Romero, Manuel, Lee, Tony, Timor, Nadav, Ding, Jennifer, Schlesinger, Claire, Schoelkopf, Hailey, Ebert, Jan, Dao, Tri, Mishra, Mayank, Gu, Alex, Robinson, Jennifer, Anderson, Carolyn Jane, Dolan-Gavitt, Brendan, Contractor, Danish, Reddy, Siva, Fried, Daniel, Bahdanau, Dzmitry, Jernite, Yacine, Ferrandis, Carlos Muñoz, Hughes, Sean, Wolf, Thomas, Guha, Arjun, von Werra, Leandro, and de Vries, Harm
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Programming Languages ,Computer Science - Software Engineering - Abstract
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context length, infilling capabilities and fast large-batch inference enabled by multi-query attention. StarCoderBase is trained on 1 trillion tokens sourced from The Stack, a large collection of permissively licensed GitHub repositories with inspection tools and an opt-out process. We fine-tuned StarCoderBase on 35B Python tokens, resulting in the creation of StarCoder. We perform the most comprehensive evaluation of Code LLMs to date and show that StarCoderBase outperforms every open Code LLM that supports multiple programming languages and matches or outperforms the OpenAI code-cushman-001 model. Furthermore, StarCoder outperforms every model that is fine-tuned on Python, can be prompted to achieve 40\% pass@1 on HumanEval, and still retains its performance on other programming languages. We take several important steps towards a safe open-access model release, including an improved PII redaction pipeline and a novel attribution tracing tool, and make the StarCoder models publicly available under a more commercially viable version of the Open Responsible AI Model license.
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- 2023
27. Data Portraits: Recording Foundation Model Training Data
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Marone, Marc and Van Durme, Benjamin
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Computer Science - Machine Learning ,Computer Science - Computation and Language - Abstract
Foundation models are trained on increasingly immense and opaque datasets. Even while these models are now key in AI system building, it can be difficult to answer the straightforward question: has the model already encountered a given example during training? We therefore propose a widespread adoption of Data Portraits: artifacts that record training data and allow for downstream inspection. First we outline the properties of such an artifact and discuss how existing solutions can be used to increase transparency. We then propose and implement a solution based on data sketching, stressing fast and space efficient querying. Using our tools, we document a popular language modeling corpus (The Pile) and a recently released code modeling dataset (The Stack). We show that our solution enables answering questions about test set leakage and model plagiarism. Our tool is lightweight and fast, costing only 3% of the dataset size in overhead. We release a live interface of our tools at https://dataportraits.org/ and call on dataset and model creators to release Data Portraits as a complement to current documentation practices., Comment: NeurIPS 2023 Datasets and Benchmarks
- Published
- 2023
28. Cyanoacrylate glue in breast surgery: the GLUBREAST Trial
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Emanuela Esposito, Claudio Siani, Ivana Donzelli, Anna Crispo, Sergio Coluccia, Piergiacomo Di Gennaro, Assunta Luongo, Franca Avino, Alfredo Fucito, Ugo Marone, Maria Teresa Melucci, Ruggero Saponara, and Raimondo di Giacomo
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cyanoacrylate glue ,Glubran ® 2 ,axillary seroma ,axillary dissection ,breast cancer ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
IntroductionIn 2018, the National Cancer Institute of Naples has launched the GLUBREAST Trial to verify the efficacy of cyanoacrylate sealing glue to prevent or reduce seroma after axillary dissection in breast surgery. The glue is a synthetic sealant (N-Butyl-2-CyanoAcrylate+Metacryloxisulfolane) biocompatible, CE approved for internal human uses and surgical procedures. The assumed mechanism of action in breast surgery is that the glue would create a seal coating in the operative field to occlude lymphatic leaks and limit seroma formation.Materials and methodsThe trial included 180 patients scheduled for breast-conserving surgery or for radical modified mastectomy without reconstruction. Out of 180 patients, 91 were randomized to receive suction drain and sealant glue after axillary dissection (Experimental Arm), whereas 89 patients (Control Arm) received suction drain without glue.StatisticsA multivariable mixed effect model on presence of liquid drained and volume drained was calculated. Stratified models by visits were performed.ResultsThe trial ended in June 2022. Older age was associated with a higher volume of seroma drained per day (β 0.30; 95% CI: 0.00–0.60). A 5-U increase in body mass index was associated with higher daily drained seroma volume in patients who underwent breast-conserving surgery (β 5.0; 95% CI: 0.62–9.4), but not in patients who underwent mastectomy (β 2.5; 95% CI: −3.6–8.6). We did not find statistically significant differences in presence of liquid drained and volume drained among the study groups. An advantage for the Experimental Arm was observed from third and fourth to fifth outpatient visits without reaching a statistical significance (p=0.069 and p=0.072, respectively); so far, 5% of patients in the Experimental Group had clinical benefit from the glue.ConclusionsThe vast majority of data in the literature come from case series, and surgeons need a higher level of evidence to drive surgical decision-making and choose proper devices to increase patient quality of life. The GLUBREAST randomized trial tested the efficacy of cyanoacrylate sealing glue to prevent postoperative seroma in breast surgery. Although only a small number of patients benefited from sealant application, we regret to say this trial has some limitation, i.e., the prolonged presence of suction drain. Further research is warranted to better clarify the benefit of cyanoacrylate glue in breast surgery.
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- 2025
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29. The epithelial era of asthma research: knowledge gaps and future direction for patient care
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Christopher E. Brightling, Gianni Marone, Helena Aegerter, Pascal Chanez, Enrico Heffler, Ian D. Pavord, Klaus F. Rabe, Lena Uller, Del Dorscheid, the Epithelial Science Expert Group, Arnaud Bourdin, Christopher E Brightling, Marco Caminati, Julia Eckl-Dorna, Ibon Eguiluz-Gracia, Pieter Hiemstra, Oscar Palomares, Remo Poto, and Gilda Varricchi
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Diseases of the respiratory system ,RC705-779 - Abstract
The Epithelial Science Expert Group convened on 18–19 October 2023, in Naples, Italy, to discuss the current understanding of the fundamental role of the airway epithelium in asthma and other respiratory diseases and to explore the future direction of patient care. This review summarises the key concepts and research questions that were raised. As an introduction to the epithelial era of research, the evolution of asthma management throughout the ages was discussed and the role of the epithelium as an immune-functioning organ was elucidated. The role of the bronchial epithelial cells in lower airway diseases beyond severe asthma was considered, as well as the role of the epithelium in upper airway diseases such as chronic rhinosinusitis. The biology and application of biomarkers in patient care was also discussed. The Epithelial Science Expert Group also explored future research needs by identifying the current knowledge and research gaps in asthma management and ranking them by priority. It was identified that there is a need to define and support early assessment of asthma to characterise patients at high risk of severe asthma. Furthermore, a better understanding of asthma progression is required. The development of new treatments and diagnostic tests as well as the identification of new biomarkers will also be required to address the current unmet needs. Finally, an increased understanding of epithelial dysfunction will determine if we can alter disease progression and achieve clinical remission.
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- 2024
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30. Are cereal grasses a single genetic system?
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Mascher, Martin, Marone, Marina Püpke, Schreiber, Mona, and Stein, Nils
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- 2024
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31. A strainmeter array as the fulcrum of novel observatory sites along the Alto Tiberina Near Fault Observatory
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L. Chiaraluce, R. Bennett, D. Mencin, W. Johnson, M. R. Barchi, M. Bohnhoff, P. Baccheschi, A. Caracausi, C. Calamita, A. Cavaliere, A. Gualandi, E. Mandler, M. T. Mariucci, L. Martelli, S. Marzorati, P. Montone, D. Pantaleo, S. Pucci, E. Serpelloni, M. Supino, S. Stramondo, C. Hanagan, L. Van Boskirk, M. Gottlieb, G. Mattioli, M. Urbani, F. Mirabella, A. Akimbekova, S. Pierdominici, T. Wiersberg, C. Marone, L. Palmieri, and L. Schenato
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Geology ,QE1-996.5 - Abstract
Fault slip is a complex natural phenomenon involving multiple spatiotemporal scales from seconds to days to weeks. To understand the physical and chemical processes responsible for the full fault slip spectrum, a multidisciplinary approach is highly recommended. The Near Fault Observatories (NFOs) aim at providing high-precision and spatiotemporally dense multidisciplinary near-fault data, enabling the generation of new original observations and innovative scientific products. The Alto Tiberina Near Fault Observatory is a permanent monitoring infrastructure established around the Alto Tiberina fault (ATF), a 60 km long low-angle normal fault (mean dip 20°), located along a sector of the Northern Apennines (central Italy) undergoing an extension at a rate of about 3 mm yr−1. The presence of repeating earthquakes on the ATF and a steep gradient in crustal velocities measured across the ATF by GNSS stations suggest large and deep (5–12 km) portions of the ATF undergoing aseismic creep. Both laboratory and theoretical studies indicate that any given patch of a fault can creep, nucleate slow earthquakes, and host large earthquakes, as also documented in nature for certain ruptures (e.g., Iquique in 2014, Tōhoku in 2011, and Parkfield in 2004). Nonetheless, how a fault patch switches from one mode of slip to another, as well as the interaction between creep, slow slip, and regular earthquakes, is still poorly documented by near-field observation. With the strainmeter array along the Alto Tiberina fault system (STAR) project, we build a series of six geophysical observatory sites consisting of 80–160 m deep vertical boreholes instrumented with strainmeters and seismometers as well as meteorological and GNSS antennas and additional seismometers at the surface. By covering the portions of the ATF that exhibits repeated earthquakes at shallow depth (above 4 km) with these new observatory sites, we aim to collect unique open-access data to answer fundamental questions about the relationship between creep, slow slip, dynamic earthquake rupture, and tectonic faulting.
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- 2024
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32. Relative performance of Neural Networks and Binary Logistic Regression in a Variable Selection framework.
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Castro Gbêmêmali Hounmenou, Emile Codjo Agbangba, Génevieve Amagbégnon, and Reine Marie Ndéla Marone
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- 2024
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33. "According to . . . ": Prompting Language Models Improves Quoting from Pre-Training Data.
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Orion Weller, Marc Marone, Nathaniel Weir, Dawn J. Lawrie, Daniel Khashabi, and Benjamin Van Durme
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- 2024
34. Harvesting Biofuels with Microbial Electrochemical Technologies (METs): State of the Art and Future Challenges
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Marandola, Clara, Cristiani, Lorenzo, Zeppilli, Marco, Villano, Marianna, Majone, Mauro, Fantini, Elio, Daddiego, Loretta, Lopez, Loredana, Ciccoli, Roberto, Signorini, Antonella, Rosa, Silvia, Marone, Antonella, Kostianoy, Andrey G., Series Editor, Carpenter, Angela, Editorial Board Member, Younos, Tamim, Editorial Board Member, Scozzari, Andrea, Editorial Board Member, Vignudelli, Stefano, Editorial Board Member, Kouraev, Alexei, Editorial Board Member, Alcaraz Gonzalez, Victor, editor, Flores Estrella, René Alejandro, editor, Haarstrick, Andreas, editor, and Gonzalez Alvarez, Victor, editor
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- 2024
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35. Performance of cross-flow turbines with varying blade materials and unsupported blade span
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Marone, Nicole, Barrington, Matthew, Gunawan, Budi, McEntee, Jarlath, and Wosnik, Martin
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- 2025
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36. Impact of emotional abuse on eating disorder psychopathology: A multiple mediation analysis
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Barone Eugenia, Carfagno Marco, Marafioti Niccolò, Bello Rosaria, Arsenio Eleonora, Marone Luigi, Volpicelli Antonio, Cascino Giammarco, and Monteleone Alessio Maria
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Eating disorders ,Childhood maltreatment ,Emotional abuse ,Psychopathology ,Mediation analysis ,Psychiatry ,RC435-571 - Abstract
Introduction: Childhood maltreatment, particularly emotional abuse (EA), has been identified as a significant risk factor for the development of eating disorders (EDs). This study investigated the association between EA and ED symptoms while considering multiple potential mediators. Methods: Participants included 151 individuals with Anorexia Nervosa (AN), 115 with Bulimia Nervosa (BN), and 108 healthy controls. The Childhood trauma questionnaire, the Toronto Alexithymia scale, the Behavioral inhibition System, and the Eating Disorder Inventory 2 scale were completed before treatment. A mediator path model was conducted in each group: EA was set as independent variable, eating symptoms as dependent variables and ineffectiveness, sensitivity to punishment, alexithymia, and impulsivity as mediators. Results: In individuals with AN, impulsivity emerged as a significant mediator between EA and desire for thinness and bulimic behaviors. Conversely, in individuals with BN, sensitivity to punishment was found to mediate the association between EA and dissatisfaction with one's body.Ineffectiveness and difficulty identifying emotions were identified as transdiagnostic mediators in both clinical groups. No mediation effect was found in healthy individuals. Discussion: The simultaneous assessment of multiple mediators in a unique model outlines the complex interplay between childhood EA and ED psychopathology. Improving ineffectiveness, emotion identification, sensitivity to punishment and impulsivity and exploring their relations with early emotional abuse may represent treatment targets in individuals with EDs and childhood trauma.
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- 2024
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37. Neutrophil exhaustion and impaired functionality in psoriatic arthritis patients
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Luca Modestino, Manuela Tumminelli, Ilaria Mormile, Leonardo Cristinziano, Annagioia Ventrici, Marialuisa Trocchia, Anne Lise Ferrara, Francesco Palestra, Stefania Loffredo, Gianni Marone, Francesca Wanda Rossi, Amato de Paulis, and Maria Rosaria Galdiero
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neutrophils ,neutrophil extracellular traps ,psoriatic arthritis ,inflammation ,innate immunity ,Immunologic diseases. Allergy ,RC581-607 - Abstract
BackgroundNeutrophils (polymorphonuclear leukocytes, PMNs) are the most abundant subtype of white blood cells and are among the main actors in the inflammatory response. Psoriatic arthritis (PsA) is a chronic inflammatory disease affecting both the axial and peripheral joints. Typically associated with psoriasis, PsA can also affect multiple systems and organs, including the nails and entheses. Despite the involvement of PMNs in PsA, their specific role in the disease remains poorly understood. This study aimed to characterize the biological functions of PMNs and neutrophil-related mediators in PsA patients.Materials and methods31 PsA patients and 22 healthy controls (HCs) were prospectively recruited. PMNs were isolated from peripheral blood and subjected to in vitro stimulation with lipopolysaccharide (LPS), N-Formylmethionyl-leucyl-phenylalanine (fMLP), tumor necrosis factor (TNF), phorbol 12-myristate 13-acetate (PMA), or control medium. Highly purified peripheral blood PMNs (>99%) were evaluated for activation status, reactive oxygen species (ROS) production, phagocytic activity, granular enzyme and neutrophil extracellular traps (NETs) release. Serum levels of matrix metalloproteinase-9 (MMP-9), myeloperoxidase (MPO), TNF, interleukin 23 (IL-23), and interleukin 17 (IL-17) were measured by ELISA. Serum Citrullinated histone H3 (CitH3) was measured as a NET biomarker.ResultsActivated PMNs from PsA patients displayed reduced activation, decreased ROS production, and impaired phagocytic activity upon stimulation with TNF, compared to HCs. PMNs from PsA patients also displayed reduced granular enzyme (MPO) and NET release. Serum analyses revealed elevated levels of MMP-9, MPO, TNF, IL-23, IL-17, and CitH3 in PsA patients compared to HCs. Serum CitH3 levels positively correlated with MPO and TNF concentrations, and IL-17 concentrations were positively correlated with IL-23 levels in PsA patients. These findings indicate that PMNs from PsA patients show reduced in vitro activation and function, and an increased presence of neutrophil-derived mediators (MMP-9, MPO, TNF, IL-23, IL-17, and CitH3) in their serum.ConclusionsTaken together, our findings suggest that PMNs from PsA patients exhibit an “exhausted” phenotype, highlighting their plasticity and multifaceted roles in PsA pathophysiology.
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- 2024
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38. Pretrained Models for Multilingual Federated Learning
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Weller, Orion, Marone, Marc, Braverman, Vladimir, Lawrie, Dawn, and Van Durme, Benjamin
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Computer Science - Computation and Language - Abstract
Since the advent of Federated Learning (FL), research has applied these methods to natural language processing (NLP) tasks. Despite a plethora of papers in FL for NLP, no previous works have studied how multilingual text impacts FL algorithms. Furthermore, multilingual text provides an interesting avenue to examine the impact of non-IID text (e.g. different languages) on FL in naturally occurring data. We explore three multilingual language tasks, language modeling, machine translation, and text classification using differing federated and non-federated learning algorithms. Our results show that using pretrained models reduces the negative effects of FL, helping them to perform near or better than centralized (no privacy) learning, even when using non-IID partitioning., Comment: NAACL 2022
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- 2022
39. Territorial brand equity in the wine market and the role of the organic label: A consumer perspective
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Dominici, Andrea, Boncinelli, Fabio, Marone, Enrico, and Casini, Leonardo
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- 2025
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40. Stochastic Chaos and Predictability in Laboratory Earthquakes
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Gualandi, Adriano, Faranda, Davide, Marone, Chris, Cocco, Massimo, and Mengaldo, Gianmarco
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Nonlinear Sciences - Chaotic Dynamics - Abstract
Laboratory earthquakes exhibit characteristics of a low dimensional random attractor with a dimension similar to that of natural slow earthquakes. A model of stochastic differential equations based on rate and state-dependent friction explains the laboratory observations. We study the transition from stable sliding to stickslip events and find that aperiodic behavior can be explained by small perturbations in the stress state. Friction's nonlinear nature amplifies small scale perturbations, reducing the predictability of the otherwise periodic macroscopic dynamics.
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- 2022
41. Deep learning for laboratory earthquake prediction and autoregressive forecasting of fault zone stress
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Laurenti, Laura, Tinti, Elisa, Galasso, Fabio, Franco, Luca, and Marone, Chris
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Physics - Geophysics ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Earthquake forecasting and prediction have long and in some cases sordid histories but recent work has rekindled interest based on advances in early warning, hazard assessment for induced seismicity and successful prediction of laboratory earthquakes. In the lab, frictional stick-slip events provide an analog for earthquakes and the seismic cycle. Labquakes are ideal targets for machine learning (ML) because they can be produced in long sequences under controlled conditions. Recent works show that ML can predict several aspects of labquakes using fault zone acoustic emissions. Here, we generalize these results and explore deep learning (DL) methods for labquake prediction and autoregressive (AR) forecasting. DL improves existing ML methods of labquake prediction. AR methods allow forecasting at future horizons via iterative predictions. We demonstrate that DL models based on Long-Short Term Memory (LSTM) and Convolution Neural Networks predict labquakes under several conditions, and that fault zone stress can be predicted with fidelity, confirming that acoustic energy is a fingerprint of fault zone stress. We predict also time to start of failure (TTsF) and time to the end of Failure (TTeF) for labquakes. Interestingly, TTeF is successfully predicted in all seismic cycles, while the TTsF prediction varies with the amount of preseismic fault creep. We report AR methods to forecast the evolution of fault stress using three sequence modeling frameworks: LSTM, Temporal Convolution Network and Transformer Network. AR forecasting is distinct from existing predictive models, which predict only a target variable at a specific time. The results for forecasting beyond a single seismic cycle are limited but encouraging. Our ML/DL models outperform the state-of-the-art and our autoregressive model represents a novel framework that could enhance current methods of earthquake forecasting., Comment: Published in https://www.sciencedirect.com/science/article/pii/S0012821X22004617
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- 2022
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42. Sensing and Degradation of Organophosphorus Compounds by Exploitation of Heat-Loving Enzymes
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Giuseppe Manco, Eros A. Lampitella, Nagendra S. K. Achanta, Giuliana Catara, Maria Marone, and Elena Porzio
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organophosphate pesticides ,chemical warfare agents ,biosensor ,thermostable enzyme ,esterases ,Phosphotriesterase-like Lactonases ,Biochemistry ,QD415-436 - Abstract
The increasing incidence of organophosphate (OP) pesticide poisoning and the use of OP chemical warfare agents (CWA) in conflicts and terrorist acts need sustainable methods for sensing, decontamination, and detoxification of OP compounds. Enzymes can serve as specific, cost-effective biosensors for OPs. We will report on recent advancements in the use of carboxylesterases from the Hormone-Sensitive Lipase for the detection of OP compounds. In addition, enzymatic-based OP detoxification and decontamination offer long-term, environmentally friendly benefits compared to conventional methods such as chemical treatment, incineration, neutralization, and volatilization. Enzymatic detoxification has gained attention as an alternative to traditional OP-detoxification methods. This review provides an overview of the latest research on enzymatic sensing and detoxification of OPs, by exploiting enzymes, isolated from thermophilic/extremophilic Bacteria and Archaea that show exceptional thermal stability and stability in other harsh conditions. Finally, we will make examples of integration between sensing and decontamination systems, including protein engineering to enhance OP-degrading activities and detailed characterization of the best variants.
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- 2025
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43. Drivers of Seasonal Change of Avian Communities in Urban Parks and Cemeteries of Latin America
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Lucas M. Leveau, Lucia Bocelli, Sergio Gabriel Quesada-Acuña, César González-Lagos, Pablo Gutierrez Tapia, Gabriela Franzoi Dri, Carlos A. Delgado-V, Alvaro Garitano-Zavala, Jackeline Campos, Yanina Benedetti, Rubén Ortega-Álvarez, Anotnio Isain Contreras-Rodríguez, Daniela Souza López, Carla Suertegaray Fontana, Thaiane Weinert da Silva, Sarah S. Zalewski Vargas, Maria C. B. Toledo, Juan Andres Sarquis, Alejandro Giraudo, Ada Lilian Echevarria, María Elisa Fanjul, María Valeria Martínez, Josefina Haedo, Luis Gonzalo Cano Sanz, Yuri A. Peña Dominguez, Viviana Fernandez-Maldonado, Veronica Marinero, Vinícius Abilhoa, Rafael Amorin, Juan Fernando Escobar-Ibáñez, María Dolores Juri, Sergio R. Camín, Luis Marone, Augusto João Piratelli, Alexandre G. Franchin, Larissa Crispim, and Federico Morelli
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biogeography ,birds ,climate ,macroecology ,Neotropical Region ,urbanization ,Veterinary medicine ,SF600-1100 ,Zoology ,QL1-991 - Abstract
Urban parks and cemeteries constitute hot spots of bird diversity in urban areas. However, the seasonal dynamics of their bird communities have been scarcely explored at large scales. This study aims to analyze the drivers of urban bird assemblage seasonality in urban parks and cemeteries comparing assemblages during breeding and non-breeding seasons in the Neotropical Region. Since cemeteries have less human disturbance than urban parks, we expected differences in bird community seasonality between habitats. The seasonal change of species composition was partitioned into species turnover and nestedness. At large scales, the seasonal change of species composition was positively related to temperature seasonality and was higher in the Northern Hemisphere. At the landscape scale, the seasonal change of composition decreased in sites located in the most urbanized areas. At the local scale, sites with the highest habitat diversity and pedestrian traffic had the lowest seasonal change of composition. The species turnover was higher in the Northern Hemisphere, augmented with increasing annual temperature range, and decreased in urban parks. The species nestedness was positively related to habitat diversity. Our results showed that a multi-scale framework is essential to understand the seasonal changes of bird communities. Moreover, the two components of seasonal composition dissimilarity showed contrasting responses to environmental variables. Although the surrounding urbanization lowered the seasonal dynamics of urban green areas, cemeteries seem to conserve more seasonal changes than urban parks. Thus, urban cemeteries help to conserve the temporal dynamics of bird communities in cities.
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- 2024
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44. Forced expression of the non-coding RNA miR-17∼92 restores activation and function in CD28-deficient CD4+ T cells
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Dölz, Marianne, Hasiuk, Marko, Gagnon, John D, Kornete, Mara, Marone, Romina, Bantug, Glenn, Kageyama, Robin, Hess, Christoph, Ansel, K Mark, Seyres, Denis, Roux, Julien, and Jeker, Lukas T
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Biological Sciences ,Biomedical and Clinical Sciences ,Medicinal and Biomolecular Chemistry ,Chemical Sciences ,Immunology ,Genetics ,Biotechnology ,2.1 Biological and endogenous factors ,Biological sciences ,immunology ,molecular mechanism of gene regulation - Abstract
CD28 provides the prototypical costimulatory signal required for productive T-cell activation. Known molecular consequences of CD28 costimulation are mostly based on studies of protein signaling molecules. The microRNA cluster miR-17∼92 is induced by T cell receptor stimulation and further enhanced by combined CD28 costimulation. We demonstrate that transgenic miR-17∼92 cell-intrinsically largely overcomes defects caused by CD28 deficiency. Combining genetics, transcriptomics, bioinformatics, and biochemical miRNA:mRNA interaction maps we empirically validate miR-17∼92 target genes that include several negative regulators of T cell activation. CD28-deficient T cells exhibit derepressed miR-17∼92 target genes during activation. CRISPR/Cas9-mediated ablation of the miR-17∼92 targets Pten and Nrbp1 in naive CD28-/- CD4+ T cells differentially increases proliferation and expression of the activation markers CD25 and CD44, respectively. Thus, we propose that miR-17∼92 constitutes a central mediator for T cell activation, integrating signals by the TCR and CD28 costimulation by dampening multiple brakes that prevent T cell activation.
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- 2022
45. Dissecting durum wheat time to anthesis into physiological traits using a QTL-based model
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Martre, Pierre, Motzo, Rosella, Mastrangelo, Anna Maria, Marone, Daniela, De Vita, Pasquale, and Giunta, Francesco
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- 2024
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46. The Ultra–Low-Profile Minos Endograft in Abdominal Aortic Aneurysms with Standard and Hostile Anatomy. A Multicenter Retrospective Study
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Marone, Enrico Maria, Cognolato, Diego, Perkmann, Reinhold, Brioschi, Chiara, Molon, Elena, Coppi, Giovanni, and Rinaldi, Luigi Federico
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- 2024
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47. Implementation of an antimicrobial stewardship program in the Vascular Surgery ward of a university tertiary care hospital in Pavia, Northern Italy
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Vecchia, Marco, Colaneri, Marta, Sacchi, Paolo, Marvulli, Lea Nadia, Salvaderi, Andrea, Lanza, Jessica, Boschini, Stefano, Ragni, Franco, Marone, Piero, Cutti, Sara, Muzzi, Alba, Marena, Carlo, Calvi, Monica, Scudeller, Luigia, Marone, Enrico Maria, and Bruno, Raffaele
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- 2023
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48. The JAK1/JAK2 inhibitor ruxolitinib inhibits mediator release from human basophils and mast cells
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Remo Poto, Leonardo Cristinziano, Gjada Criscuolo, Caterina Strisciuglio, Francesco Palestra, Gianluca Lagnese, Antonio Di Salvatore, Gianni Marone, Giuseppe Spadaro, Stefania Loffredo, and Gilda Varricchi
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asthma ,basophil ,histamine ,IL-4 ,IL-13 ,mast cell ,Immunologic diseases. Allergy ,RC581-607 - Abstract
IntroductionThe Janus kinase (JAK) family includes four cytoplasmic tyrosine kinases (JAK1, JAK2, JAK3, and TYK2) constitutively bound to several cytokine receptors. JAKs phosphorylate downstream signal transducers and activators of transcription (STAT). JAK-STAT5 pathways play a critical role in basophil and mast cell activation. Previous studies have demonstrated that inhibitors of JAK-STAT pathway blocked the activation of mast cells and basophils.MethodsIn this study, we investigated the in vitro effects of ruxolitinib, a JAK1/2 inhibitor, on IgE- and IL-3-mediated release of mediators from human basophils, as well as substance P-induced mediator release from skin mast cells (HSMCs).ResultsRuxolitinib concentration-dependently inhibited IgE-mediated release of preformed (histamine) and de novo synthesized mediators (leukotriene C4) from human basophils. Ruxolitinib also inhibited anti-IgE- and IL-3-mediated cytokine (IL-4 and IL-13) release from basophils, as well as the secretion of preformed mediators (histamine, tryptase, and chymase) from substance P-activated HSMCs.DiscussionThese results indicate that ruxolitinib, inhibiting the release of several mediators from human basophils and mast cells, is a potential candidate for the treatment of inflammatory disorders.
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- 2024
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49. Physicians’ preferences for radioiodine treatment of differentiated thyroid cancer in Brazil: an observational study
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Rosália do Prado Padovani, Isabella Fagian Pansani, Marília Martins Silveira Marone, Fernanda Vaisman, Ana Luiza Silva Maia, José Miguel Silva Dora, Helton Estrela Ramos, Ana Amélia Fialho de Oliveira Hoff, and George Barbério Coura Filho
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Thyroid nodule ,thyroid neoplasms ,radiopharmaceuticals ,thyroid cancer, papillary thyroid carcinoma ,thyrotropin ,thyroid diseases ,Medicine ,Diseases of the endocrine glands. Clinical endocrinology ,RC648-665 - Abstract
ABSTRACT Objective The aim of this observational, cross-sectional study was to investigate physicians’ preferences for radioiodine (RAI) treatment in patients with differentiated thyroid cancer (DTC) in Brazil and the factors influencing RAI indications. Materials and methods A survey was distributed to physicians potentially involved in DTC care in Brazil to understand the factors influencing RAI indications. The survey collected information on the profiles of the physicians, along with the characteristics of their workplaces and their preferences regarding RAI indications in three hypothetical clinical cases. Cases 1, 2, and 3 described the cases of patients with DTC and variations to the case that included different scenarios to assess how the respondents would change their RAI recommendations. The analysis included the RAI indications across different medical specialties. Results A total of 175 physicians answered the survey. There was considerable variability in RAI recommendations in all three cases. The training background influenced the respondents' preferences for RAI indications and their approaches to preparing patients for RAI treatment. Conclusion The findings of this study reaffirm the need for a Brazilian consensus among physicians across multiple specialties to help guide health care professionals treating patients with DTC in Brazil.
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- 2024
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50. Age management and intergenerational education in health. Artificial intelligence and virtual
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Francesca Marone and Maria Navarra
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Age Management ,healthcare contexts ,active policies ,continuous training ,sanità ,politiche attive ,Education - Abstract
In recent years, age management practices and strategies have become widely diffused since today the valorization of people according to their age represents, a fundamental aspect for organisations, which are required to understand in depth the dynamics of generational belonging for a correct definition of their work and training policies. Population ageing is a phenomenon shared by many countries, especially those in Europe. In health care contexts, the ageing of workers and their co-habitation of organisational contexts with colleagues belonging to other generations demands effective equal opportunities for training and skills development policies to improve both the quality of work and the quality of services offered. To this purpose, communities of practice, including virtual ones, become a training device to be explored, especially looking at the latest developments in artificial intelligence. Age management e formazione intergenerazionale in medicina. Intelligenza artificiale e comunità di pratica virtuali. Negli ultimi anni, le pratiche e le strategie di age management si sono largamente diffuse poiché la valorizzazione delle persone in funzione della loro età rappresenta, oggi, un aspetto fondamentale per le organizzazioni, chiamate a comprendere in modo approfondito le dinamiche dell’appartenenza generazionale per una corretta definizione e valorizzazione delle proprie politiche di lavoro e formazione. L’invecchiamento della popolazione è un fenomeno che accomuna molti paesi, soprattutto quelli europei. Nei contesti sanitari, l’invecchiamento degli operatori e la loro co-abitazione dei contesti organizzativi con colleghi appartenenti ad altre generazioni richiede politiche efficaci di pari opportunità e di formazione e sviluppo delle competenze per migliorare sia la qualità del lavoro sia la qualità dei servizi offerti. A tale scopo, le comunità di pratica, anche quelle virtuali, divengono un dispositivo formativo da esplorare, soprattutto guardando ai più recenti sviluppi dell’intelligenza artificiale.
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- 2024
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