22,491 results on '"Orsi A"'
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2. Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants
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Borges, Beatriz, Foroutan, Negar, Bayazit, Deniz, Sotnikova, Anna, Montariol, Syrielle, Nazaretzky, Tanya, Banaei, Mohammadreza, Sakhaeirad, Alireza, Servant, Philippe, Neshaei, Seyed Parsa, Frej, Jibril, Romanou, Angelika, Weiss, Gail, Mamooler, Sepideh, Chen, Zeming, Fan, Simin, Gao, Silin, Ismayilzada, Mete, Paul, Debjit, Schöpfer, Alexandre, Janchevski, Andrej, Tiede, Anja, Linden, Clarence, Troiani, Emanuele, Salvi, Francesco, Behrens, Freya, Orsi, Giacomo, Piccioli, Giovanni, Sevel, Hadrien, Coulon, Louis, Pineros-Rodriguez, Manuela, Bonnassies, Marin, Hellich, Pierre, van Gerwen, Puck, Gambhir, Sankalp, Pirelli, Solal, Blanchard, Thomas, Callens, Timothée, Aoun, Toni Abi, Alonso, Yannick Calvino, Cho, Yuri, Chiappa, Alberto, Sclocchi, Antonio, Bruno, Étienne, Hofhammer, Florian, Pescia, Gabriel, Rizk, Geovani, Dadi, Leello, Stoffl, Lucas, Ribeiro, Manoel Horta, Bovel, Matthieu, Pan, Yueyang, Radenovic, Aleksandra, Alahi, Alexandre, Mathis, Alexander, Bitbol, Anne-Florence, Faltings, Boi, Hébert, Cécile, Tuia, Devis, Maréchal, François, Candea, George, Carleo, Giuseppe, Chappelier, Jean-Cédric, Flammarion, Nicolas, Fürbringer, Jean-Marie, Pellet, Jean-Philippe, Aberer, Karl, Zdeborová, Lenka, Salathé, Marcel, Jaggi, Martin, Rajman, Martin, Payer, Mathias, Wyart, Matthieu, Gastpar, Michael, Ceriotti, Michele, Svensson, Ola, Lévêque, Olivier, Ienne, Paolo, Guerraoui, Rachid, West, Robert, Kashyap, Sanidhya, Piazza, Valerio, Simanis, Viesturs, Kuncak, Viktor, Cevher, Volkan, Schwaller, Philippe, Friedli, Sacha, Jermann, Patrick, Kaser, Tanja, and Bosselut, Antoine
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Computer Science - Computers and Society ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they also pose significant challenges for assessment and learning outcomes. We conceptualize these challenges through the lens of vulnerability, the potential for university assessments and learning outcomes to be impacted by student use of generative AI. We investigate the potential scale of this vulnerability by measuring the degree to which AI assistants can complete assessment questions in standard university-level STEM courses. Specifically, we compile a novel dataset of textual assessment questions from 50 courses at EPFL and evaluate whether two AI assistants, GPT-3.5 and GPT-4 can adequately answer these questions. We use eight prompting strategies to produce responses and find that GPT-4 answers an average of 65.8% of questions correctly, and can even produce the correct answer across at least one prompting strategy for 85.1% of questions. When grouping courses in our dataset by degree program, these systems already pass non-project assessments of large numbers of core courses in various degree programs, posing risks to higher education accreditation that will be amplified as these models improve. Our results call for revising program-level assessment design in higher education in light of advances in generative AI., Comment: 20 pages, 8 figures
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- 2024
3. Multi-Resolution Histopathology Patch Graphs for Ovarian Cancer Subtyping
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Breen, Jack, Allen, Katie, Zucker, Kieran, Orsi, Nicolas M., and Ravikumar, Nishant
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Computer vision models are increasingly capable of classifying ovarian epithelial cancer subtypes, but they differ from pathologists by processing small tissue patches at a single resolution. Multi-resolution graph models leverage the spatial relationships of patches at multiple magnifications, learning the context for each patch. In this study, we conduct the most thorough validation of a graph model for ovarian cancer subtyping to date. Seven models were tuned and trained using five-fold cross-validation on a set of 1864 whole slide images (WSIs) from 434 patients treated at Leeds Teaching Hospitals NHS Trust. The cross-validation models were ensembled and evaluated using a balanced hold-out test set of 100 WSIs from 30 patients, and an external validation set of 80 WSIs from 80 patients in the Transcanadian Study. The best-performing model, a graph model using 10x+20x magnification data, gave balanced accuracies of 73%, 88%, and 99% in cross-validation, hold-out testing, and external validation, respectively. However, this only exceeded the performance of attention-based multiple instance learning in external validation, with a 93% balanced accuracy. Graph models benefitted greatly from using the UNI foundation model rather than an ImageNet-pretrained ResNet50 for feature extraction, with this having a much greater effect on performance than changing the subsequent classification approach. The accuracy of the combined foundation model and multi-resolution graph network offers a step towards the clinical applicability of these models, with a new highest-reported performance for this task, though further validations are still required to ensure the robustness and usability of the models., Comment: Initially submitted version of a paper which has been accepted in the GRAIL workshop at MICCAI 2024
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- 2024
4. End-to-End simulation framework for astronomical spectrographs: SOXS, CUBES and ANDES
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Scaudo, A., Genoni, M., Causi, G. Li, Cabona, L., Landoni, M., Campana, S., Schipani, P., Claudi, R., Aliverti, M., Baruffolo, A., Ben-Ami, S., Biondi, F., Capasso, G., Cosentino, R., D'Alessio, F., D'Avanzo, P., Hershko, O., Kuncarayakti, H., Munari, M., Santhakumari, K. Radhakrishnan, Pignata, G., Rubin, A., Scuderi, S., Vitali, F., Young, D., Achrén, J., Araiza-Duran, J. A., Arcavi, I., Battaini, F., Brucalassi, A., Bruch, R., Cappellaro, E., Colapietro, M., Della Valle, M., De Pascale, M., Di Benedetto, R., D'Orsi, S., Gal-Yam, A., Hernandez, M., Kotilainen, J., Marty, L., Mattila, S., Rappaport, M., Ricci, D., Riva, M., Salasnich, B., Smartt, S., Sanchez, R. Zanmar, Stritzinger, M., Ventura, H., Cupani, G., Porru, M., Franchini, M., Cirami, R., Calderone, G., Covino, S., Smiljanic, R., Monteiro, M., Balestra, A., Sordo, R., Mason, E., Rousseu, S., Leão, I. de Castro, Zanutta, A., Martins, A. de Meideros, Sosnowska, D., Marquart, T., Boisse, I., Sousa, S., Hernandez, J., Piskunov, N., Puschnig, J., Senna, N., Martins, B., Di Marcantonio, P., and Marconi, A.
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
We present our numerical simulation approach for the End-to-End (E2E) model applied to various astronomical spectrographs, such as SOXS (ESO-NTT), CUBES (ESO-VLT), and ANDES (ESO-ELT), covering multiple wavelength regions. The E2E model aim at simulating the expected astronomical observations starting from the radiation of the scientific sources (or calibration sources) up to the raw-frame data produced by the detectors. The comprehensive description includes E2E architecture, computational models, and tools for rendering the simulated frames. Collaboration with Data Reduction Software (DRS) teams is discussed, along with efforts to meet instrument requirements. The contribution to the cross-correlation algorithm for the Active Flexure Compensation (AFC) system of CUBES is detailed., Comment: 19 pages, 17 figures, SPIE Astronomical Telescopes + Instrumentation, Yokohama 2024. arXiv admin note: text overlap with arXiv:2209.07185, arXiv:2012.12684
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- 2024
5. Final Alignment and Image Quality Test for the Acquisition and Guiding System of SOXS
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Araiza-Duran, J. A., Pignata, G., Brucalassi, A., Aliverti, M., Battaini, F., Radhakrishnan, K., Di Filippo, S., Lessio, L., Claudi, R., Ricci, D., Colapietro, M., Cosentino, R., D'Orsi, S., Munari, M., Dima, M., Schipani, P., Campana, S., Baruffolo, A., Sanchez, R. Zanmar, Riva, M., Genoni, M., Ben-Ami, S., Rubin, A., Bruch, R., Capasso, G., D'Alessio, F., D'Avanzo, P., Hershko, O., Kuncarayakti, H., Landoni, M., Scuderi, S., Vitali, F., Young, D., Achren, J., Arcavi, I., Cappellaro, E., Della Valle, M., Di Benedetto, R., Gal-Yam, A., Diaz, M. Hernandez, Kotilainen, J., Causi, G. Li, Marty, L., Mattila, S., Rappaport, M., Salasnich, B., Smartt, S., Stritzinger, M., Ventura, H. Perez, Asquini, L., Bichkovsky, A., Savarese, S., and Cabona, L.
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
SOXS (Son Of X-Shooter) will be the new medium-resolution (R 4500 for 1 slit), high-efficiency, wide-band spectrograph for the ESO NTT at La Silla Observatory, Chile. It will be dedicated to the follow-up of any kind of transient events, ensuring fast time, high efficiency, and availability. It consists of a central structure (common path) that supports two spectrographs optimized for the UV-Visible and a Near-Infrared range. Attached to the common path is the Acquisition and Guiding Camera system (AC), equipped with a filter wheel that can provide science-grade imaging and moderate high-speed photometry. The AC Unit was integrated and aligned during the summer months of 2022 and has since been mounted in the NTTs telescope simulator. This work gives an update on the Acquisition Camera Unit status, describes the Image Quality Tests that were performed, and discusses the AC Optical Performance., Comment: SPIE Proceedings Volume 13096, Ground-based and Airborne Instrumentation for Astronomy X; 1309672 (2024)
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- 2024
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6. The integration of the SOXS control electronics towards the PAE
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Colapietro, Mirko, D'Orsi, Sergio, Capasso, Giulio, Savarese, Salvatore, Schipani, Pietro, Marty, Laurent, Sanchez, Ricardo Zanmar, Aliverti, Matteo, Battaini, Federico, Di Filippo, Simone, Santhakumari, Kalyan Kumar Radhakrishnan, Ricci, Davide, Salasnich, Bernardo, Campana, Sergio, Claudi, Riccardo, Araiza-Duran, Jose, Baruffolo, Andrea, Ami, Sagi Ben, Bichkovsky, Alex, Brucalassi, Anna, Cosentino, Rosario, D'Alessio, Francesco, D'Avanzo, Paolo, Di Benedetto, Rosario, Genoni, Matteo, Hershko, Ofir, Kuncarayakti, Hanindyo, Lessio, Luigi, Martinetti, Eugenio, Micciche, Antonio, Nicotra, Gaetano, Pignata, Giuliano, Rubin, Adam, Scuderi, Salvatore, Vitali, Fabrizio, Achren, Jani, Arcavi, Iair, Asquini, Laura, Bruch, Rachel, Cappellaro, Enrico, Della Valle, Massimo, Gal-Yam, Avishay, Diaz, Marcos Hernandez, Kotilainen, Jari, Landoni, Marco, Causi, Gianluca Li, Mattila, Seppo, Munari, Matteo, Ventura, Hector Perez, Rappaport, Michael, Riva, Marco, Smartt, Steven, Stritzinger, Maximilian, and Young, David
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
SOXS (Son Of X-Shooter) is the new single object spectrograph for the ESO New Technology Telescope (NTT) at the La Silla Observatory, able to cover simultaneously both the UV-VIS and NIR bands (350-2000 nm). The instrument is currently in the integration and test phase, approaching the Preliminary Acceptance in Europe (PAE) before shipment to Chile for commissioning. After the assembly and preliminary test of the control electronics at INAF - Astronomical Observatory of Capodimonte (Napoli), the two main control cabinets of SOXS are now hosted in Padova, connected to the real hardware. This contribution describes the final electronic cabinets layout, the control strategy and the different integration phases, waiting for the Preliminary Acceptance in Europe and the installation of the instrument in Chile.
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- 2024
7. What is your favorite transient event? SOXS is almost ready to observe!
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Santhakumari, Kalyan Kumar Radhakrishnan, Battaini, Federico, Di Filippo, Simone, Di Rosa, Silvio, Cabona, Lorenzo, Claudi, Riccardo, Lessio, Luigi, Dima, Marco, Young, David, Landoni, Marco, Colapietro, Mirko, D'Orsi, Sergio, Aliverti, Matteo, Genoni, Matteo, Munari, Matteo, Sanchez, Ricardo Zanmar, Vitali, Fabrizio, Ricci, Davide, Schipani, Pietro, Campana, Sergio, Achren, Jani, Araiza-Duran, Jose, Arcavi, Iair, Baruffolo, Andrea, Ben-Ami, Sagi, Bitchkovsky, Alex, Brucalassi, Anna, Bruch, Rachel, Capasso, Giulio, Cappellaro, Enrico, Cosentino, Rosario, D'Alessio, Francesco, D'Avanzo, Paolo, Della Valle, Massimo, Di Benedetto, Rosario, Gal-Yam, Avishay, Diaz, Marcos Hernandez, Hershko, Ofir, Kotilainen, Jari, Kuncarayakti, Hanindyo, Causi, Gianluca Li, Marafatto, Luca, Martinetti, Eugenio, Marty, Laurent, Mattila, Seppo, Micciche, Antonio, Nicotra, Gaetano, Oggioni, Luca, Ventura, Hector Perez, Pariani, Giorgio, Pignata, Giuliano, Rappaport, Michael, Riva, Marco, Rubin, Adam, Salasnich, Bernardo, Savarese, Salvatore, Scuderi, Salvatore, Smartt, Steven, and Stritzinger, Maximilian
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Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Earth and Planetary Astrophysics - Abstract
The Son Of X-Shooter (SOXS) will be the specialized facility to observe any transient event with a flexible scheduler at the ESO New Technology Telescope (NTT) at La Silla, Chile. SOXS is a single object spectrograph offering simultaneous spectral coverage in UV-VIS (350-850 nm) and NIR (800-2000 nm) wavelength regimes with an average of R~4500 for a 1arcsec slit. SOXS also has imaging capabilities in the visible wavelength regime. Currently, SOXS is being integrated at the INAF-Astronomical Observatory of Padova. Subsystem- and system-level tests and verification are ongoing to ensure and confirm that every requirement and performance are met. In this paper, we report on the integration and verification of SOXS as the team and the instrument prepare for the Preliminary Acceptance Europe (PAE).
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- 2024
8. The status of the NIR arm of the SOXS Instrument toward the PAE
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Vitali, Fabrizio, Genoni, Matteo, Aliverti, Matteo, Radhakrishnan, Kalyan, Battaini, Federico, D'Avanzo, Paolo, D'Alessio, Francesco, Pariani, Giorgio, Oggioni, Luca, Scuderi, Salvatore, Ricci, Davide, Martinetti, Eugenio, Miccichè, Antonio, Nicotra, Gaetano, Colapietro, Mirko, D'Orsi, Sergio, Munari, Matteo, Lessio, Luigi, Di Filippo, Simone, Scaudo, Andrea, Bellassai, Giancarlo, Di Benedetto, Rosario, Occhipinti, Giovanni, Landoni, Marco, Accardo, Matteo, Mehrgan, Leander, Ives, Derek, Scirè, Carlotta, Campana, Sergio, Schipani, Pietro, Claudi, Riccardo, Capasso, Giulio, Riva, Marco, Sanchez, Ricardo Zanmar, Araiza-Durán, José Antonio, Arcavi, Iair, Baruffolo, Andrea, Ben-Ami, Sagi, Brucalassi, Anna, Bruch, Rachel, Cappellaro, Enrico, Cosentino, Rosario, De Pascale, Marco, Della Valle, Massimo, Gal-Yam, Avishay, Díaz, Marcos Hernandez, Hershko, Ofir, Kotilainen, Jari, Kuncarayakti, Hanindyo, Causi, Gianluca Li, Marty, Laurent, Mattila, Seppo, Ventura, Hector Pérez, Pignata, Giuliano, Rappaport, Michael, Rubin, Adam, Salasnich, Bernardo, Smartt, Stephen, Stritzinger, Maximilian, and Young, David
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
The Son Of X-Shooter (SOXS) is a single object spectrograph, built by an international consortium for the 3.58-m ESO New Technology Telescope at the La Silla Observatory [1]. It offers a simultaneous spectral coverage over 350-2000 nm, with two separate spectrographs. In this paper we present the status of the Near InfraRed (NIR) cryogenic echelle cross-dispersed spectrograph [1], in the range 0.80-2.00 {\mu}m with 15 orders, equipped with an 2k x 2k Hawaii H2RG IR array from Teledyne, working at 40K, that is currently assembled and tested on the SOXS instrument, in the premises of INAF in Padova. We describe the different tests and results of the cryo, vacuum, opto-mechanics and detector subsystems that finally will be part of the PAE by ESO., Comment: 8 Pages, 7 Figures, Astronomical Telescopes and Instrumentation, SPIE Proceedings 2024
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- 2024
9. Automated scheduler for the SOXS instrument: design and performance
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Asquini, Laura, Landoni, Marco, Young, Dave, Marty, Laurent, Smartt, Stephen J., Campana, Sergio, Claudi, Riccardo, Schipani, Pietro, Achren, Jani, Aliverti, Matteo, Duran, Jose A. Araiza, Arcavi, Iair, Battaini, Federico, Baruffolo, Andrea, Ami, Sagi Ben, Bianco, Andrea, Bichkovsky, Alex, Brucalassi, Anna, Bruch, Rachel, Capasso, Giulio, Cappellaro, Enrico, Colapietro, Mirko, Cosentino, Rosario, DÁlessio, Francesco, D'Avanzo, Paolo, Della Valle, Massimo, D'Orsi, Sergio, Di Benedetto, Rosario, Di Filippo, Simone, Yam, Avishay Gal, Genoni, Matteo, Hernandez, Marcos, Hershko, Ofir, Kotilainen, Jari, Kuncarayakti, Hanindyo, Causi, Gianluca Li, Mattila, Seppo, Munari, Matteo, Pariani, Giorgio, Ventura, Hector Perez, Pignata, Giuliano, Radhakrishnan, Kalyan, Rappaport, Michael, Ricci, Davide, Riva, Marco, Rubin, Adam, Salasnich, Bernardo, Savarese, Salvatore, Stritzinger, Maximilian, Scuderi, Salvatore, Vitali, Fabrizio, and Sanchez, Ricardo Zanmar
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
We present the advancements in the development of the scheduler for the Son Of X-shooter instrument at the ESO-NTT 3.58-m telescope in La Silla, Chile. SOXS is designed as a single-object spectroscopic facility and features a high-efficiency spectrograph with two arms covering the spectral range of 350-2000 nm and a mean resolving power of approximately R=4500. It will conduct UV-visible and near-infrared follow-up observations of astrophysical transients, drawing from a broad pool of targets accessible through the streaming services of wide-field telescopes, both current and future, as well as high-energy satellites. The instrument will cater to various scientific objectives within the astrophysical community, each entailing specific requirements for observation planning. SOXS will operate at the European Southern Observatory (ESO) in La Silla, without the presence of astronomers on the mountain. This poses a unique challenge for the scheduling process, demanding a fully automated algorithm that is autonomously interacting with the appropriate databases and the La Silla Weather API, and is capable of presenting the operator not only with an ordered list of optimal targets (in terms of observing constraints) but also with optimal backups in the event of changing weather conditions. This imposes the necessity for a scheduler with rapid-response capabilities without compromising the optimization process, ensuring the high quality of observations and best use of the time at the telescope. We thus developed a new highly available and scalable architecture, implementing API Restful applications like Docker Containers, API Gateway, and Python-based Flask frameworks. We provide an overview of the current state of the scheduler, which is now ready for the approaching on-site testing during Commissioning phase, along with insights into its web interface and preliminary performance tests.
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- 2024
10. Characterisation and assessment of the SOXS Spectrograph UV-VIS Detector System
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Cosentino, R., Hernandez, M., Ventura, H., Campana, S., Claudi, R., Schipani, P., Aliverti, M., Asquini, L., Baruffolo, A., Battaini, F., Ben-Ami, Sagi, Bichkovsky, A., Capasso, G., D'Alessio, F., D'Avanzo, P., Hershko, O., Kuncarayakti, H., Landoni, M., Munari, M., Pignata, G., Rubin, A., Scuderi, S., Vitali, F., Young, D., Achren, J., Araiza-Duran, J. A., Arcavi, I., Brucalassi, A., Bruch, R., Cappellaro, E., Colapietro, M., Della Valle, M., Di Benedetto, R., Di Filippo, S., D'Orsi, S., Gal-Yam, A., Genoni, M., Kotilainen, J., Causi, G. Li, Marty, L., Mattila, S., Rappaport, M., Radhakrishnan, K., Ricci, D., Riva, M., Salasnich, B., Savarese, S., Smartt, S., Sanchez, R. Zanmar, Stritzinger, M., Accardo, M., Mehrgan, L. H., and Ives, D.
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
The SOXS spectrograph, designed for the ESO NTT telescope, operates in both the optical (UV-VIS: 350-850 nm) and NIR (800-2000 nm) bands. This article provides an overview of the final tests conducted on the UV-VIS camera system using a telescope simulator. It details the system's performance evaluation, including key metrics such as gain, readout noise, and linearity, and highlights the advancements made in the upgraded acquisition system. The testing process, conducted in the Padua laboratory, involved comprehensive simulations of the telescope environment to ensure the results closely resemble those expected at the ESO-NTT telescope. The successful completion of these tests confirms the system's readiness for deployment to Chile, where it will be installed on the NTT telescope, marking a significant milestone in the SOXS project., Comment: SPIE Proceedings Volume 13096, Ground-based and Airborne Instrumentation for Astronomy X; 130962U (2024)
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- 2024
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11. SOXS NIR: Optomechanical integration and alignment, optical performance verification before full instrument assembly
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Genoni, M., Aliverti, M., Pariani, G., Oggioni, L., Vitali, F., D'Alessio, F., D'Avanzo, P., Campana, S., Munari, M., Sanchez, R. Zanmar, Scaudo, A., Landoni, M., Young, D., Scuderi, S., Schipani, P., Riva, M., Claudi, R., Radhakrishnan, K., Battaini, F., Rubin, A., Baruffolo, A., Capasso, G., Cosentino, R., Hershko, O., Kuncarayakti, H., Pignata, G., Ben-Ami, S., Brucalassi, A., Achren, J., Araiza-Duran, J. A., Arcavi, I., Asquini, L., Bruch, R., Cappellaro, E., Colapietro, M., Della Valle, M., De Pascale, M., Di Benedetto, R., D'Orsi, S., Gal-Yam, A., Diaz, M. Hernandez, Kotilainen, J., Causi, G. Li, Marty, L., Mattila, S., Rappaport, M., Ricci, D., Salasnich, B., Smartt, S., Stritzinger, M., and Ventura, H.
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
This paper presents the opto-mechanical integration and alignment, functional and optical performance verification of the NIR arm of Son Of X-Shooter (SOXS) instrument. SOXS will be a single object spectroscopic facility for the ESO-NTT 3.6-m telescope, made by two arms high efficiency spectrographs, able to cover the spectral range 350 2050 nm with a mean resolving power R~4500. In particular the NIR arm is a cryogenic echelle cross-dispersed spectrograph spanning the 780-2050 nm range. We describe the integration and alignment method performed to assemble the different opto-mechanical elements and their installation on the NIR vacuum vessel, which mostly relies on mechanical characterization. The tests done to assess the image quality, linear dispersion and orders trace in laboratory conditions are summarized. The full optical performance verification, namely echellogram format, image quality and resulting spectral resolving power in the whole NIR arm (optical path and science detector) is detailed. Such verification is one of the most relevant prerequisites for the subsequent full instrument assembly and provisional acceptance in Europe milestone, foreseen in 2024., Comment: SPIE Proceedings Volume 13096, Ground-based and Airborne Instrumentation for Astronomy X; 130962T (2024)
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- 2024
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12. Walking with SOXS towards the transient sky
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Schipani, P., Campana, S., Claudi, R., Aliverti, M., Baruffolo, A., Ben-Ami, S., Capasso, G., Colapietro, M., Cosentino, R., D'Alessio, F., D'Avanzo, P., Genoni, M., Hershko, O., Kuncarayakti, H., Landoni, M., Munari, M., Pignata, G., Radhakrishnan, K., Ricci, D., Rubin, A., Scuderi, S., Vitali, F., Young, D., Accardo, M., Achrén, J., Araiza-Durán, J. A., Arcavi, I., Asquini, L., Battaini, F., Bichkovsky, A., Brucalassi, A., Bruch, R., Cabona, L., Cappellaro, E., Della Valle, M., Di Filippo, S., Di Benedetto, R., D'Orsi, S., Gal-Yam, A., Hernandez, M., Ives, D., Kaeufl, H. -U., Kotilainen, J., Causi, G. Li, Lessio, L., Marty, L., Mattila, S., Mehrgan, L., Pasquini, L., Pompei, E., Rappaport, M., Riva, M., Salasnich, B., Savarese, S., Saviane, I., Schöller, M., Silber, A., Smartt, S., Sanchez, R. Zanmar, Stritzinger, M., Sulich, A., and Ventura, H.
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
SOXS (Son Of X-Shooter) is the new ESO instrument that is going to be installed on the 3.58-m New Technology Telescope at the La Silla Observatory. SOXS is a single object spectrograph offering a wide simultaneous spectral coverage from U- to H-band. Although such an instrument may have potentially a large variety of applications, the consortium designed it with a clear science case: it is going to provide the spectroscopic counterparts to the ongoing and upcoming imaging surveys, becoming one of the main follow-up instruments in the Southern hemisphere for the classification and characterization of transients. The NTT+SOXS system is specialized to observe all transients and variable sources discovered by imaging surveys with a flexible schedule maintained by the consortium, based on a remote scheduler which will interface with the observatory software infrastructure. SOXS is realized timely to be highly synergic with transients discovery machines like the Vera C. Rubin Observatory. The instrument has been integrated and tested in Italy, collecting and assembling subsystems coming from all partners spread over six countries in three continents. The first preparatory activities in Chile have been completed at the telescope. This article gives an updated status of the project before the shipping of the instrument to Chile., Comment: SPIE Astronomical Telescopes + Instrumentation, 2024, Yokohama, Japan
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- 2024
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13. The SOXS Instrument Control Software approaching the PAE
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Ricci, Davide, Salasnich, Bernardo, Baruffolo, Andrea, Achrén, Jani, Aliverti, Matteo, Araiza-Durán, José A., Arcavi, Iair, Asquini, Laura, Battaini, Federico, Ben-Ami, Sagi, Bichkovsky, Alex, Brucalassi, Anna, Bruch, Rachel, Cabona, Lorenzo, Campana, Sergio, Capasso, Giulio, Cappellaro, Enrico, Claudi, Riccardo, Colapietro, Mirko, Cosentino, Rosario, D'Alessio, Francesco, D'Avanzo, Paolo, D'Orsi, Sergio, Della Valle, Massimo, Di Benedetto, Rosario, Di Filippo, Simone, Gal-Yam, Avishay, Genoni, Matteo, Dıaz, Marcos Hernandez, Hershko, Ofir, Kotilainen, Jari, Kuncarayakti, Hanindyo, Landoni, Marco, Causi, Gianluca Li, Marty, Laurent, Mattila, Seppo, Munari, Matteo, Oggioni, Luca, Ventura, Hector Pérez, Pariani, Giorgio, Pignata, Giuliano, Radhakrishnan, Kalyan, Smartt, Stephen, Rappaport, Michael, Riva, Marco, Rubin, Adam, Savarese, Salvatore, Schipani, Pietro, Scuderi, Salvatore, Stritzinger, Maximilian, Vitali, Fabrizio, Young, David, and Sanchez, Ricardo Zanmar
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Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Earth and Planetary Astrophysics ,Astrophysics - High Energy Astrophysical Phenomena ,D.2.10 - Abstract
The Instrument Control Software of SOXS (Son Of X-Shooter), the forthcoming spectrograph for the ESO New Technology Telescope at the La Silla Observatory, has reached a mature state of development and is approaching the crucial Preliminary Acceptance in Europe phase. Now that all the subsystems have been integrated in the laboratories of the Padova Astronomical Observatory, the team operates for testing purposes with the whole instrument at both engineering and scientific level. These activities will make use of a set of software peculiarities that will be discussed in this contribution. In particular, we focus on the synoptic panel, the co-rotator system special device, on the Active Flexure Compensation system which controls two separate piezo tip-tilt devices., Comment: 6 pages, 3 figures, SPIE conference
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- 2024
14. Perturb-and-Project: Differentially Private Similarities and Marginals
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Cohen-Addad, Vincent, d'Orsi, Tommaso, Epasto, Alessandro, Mirrokni, Vahab, and Zhong, Peilin
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Computer Science - Machine Learning ,Computer Science - Cryptography and Security ,Computer Science - Data Structures and Algorithms ,F.2 ,G.3 - Abstract
We revisit the input perturbations framework for differential privacy where noise is added to the input $A\in \mathcal{S}$ and the result is then projected back to the space of admissible datasets $\mathcal{S}$. Through this framework, we first design novel efficient algorithms to privately release pair-wise cosine similarities. Second, we derive a novel algorithm to compute $k$-way marginal queries over $n$ features. Prior work could achieve comparable guarantees only for $k$ even. Furthermore, we extend our results to $t$-sparse datasets, where our efficient algorithms yields novel, stronger guarantees whenever $t\le n^{5/6}/\log n\,.$ Finally, we provide a theoretical perspective on why \textit{fast} input perturbation algorithms works well in practice. The key technical ingredients behind our results are tight sum-of-squares certificates upper bounding the Gaussian complexity of sets of solutions., Comment: 21 ppages, ICML 2024
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- 2024
15. Multi-View Stochastic Block Models
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Cohen-Addad, Vincent, d'Orsi, Tommaso, Lattanzi, Silvio, and Nasser, Rajai
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Computer Science - Machine Learning ,Computer Science - Data Structures and Algorithms ,Statistics - Machine Learning ,F.2 ,G.3 - Abstract
Graph clustering is a central topic in unsupervised learning with a multitude of practical applications. In recent years, multi-view graph clustering has gained a lot of attention for its applicability to real-world instances where one has access to multiple data sources. In this paper we formalize a new family of models, called \textit{multi-view stochastic block models} that captures this setting. For this model, we first study efficient algorithms that naively work on the union of multiple graphs. Then, we introduce a new efficient algorithm that provably outperforms previous approaches by analyzing the structure of each graph separately. Furthermore, we complement our results with an information-theoretic lower bound studying the limits of what can be done in this model. Finally, we corroborate our results with experimental evaluations., Comment: 31 pages, ICML 2024
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- 2024
16. A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering
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Cohen-Addad, Vincent, d'Orsi, Tommaso, and Mousavifar, Aida
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Computer Science - Data Structures and Algorithms ,Computer Science - Machine Learning ,F.2 ,G.3 - Abstract
We consider the semi-random graph model of [Makarychev, Makarychev and Vijayaraghavan, STOC'12], where, given a random bipartite graph with $\alpha$ edges and an unknown bipartition $(A, B)$ of the vertex set, an adversary can add arbitrary edges inside each community and remove arbitrary edges from the cut $(A, B)$ (i.e. all adversarial changes are \textit{monotone} with respect to the bipartition). For this model, a polynomial time algorithm is known to approximate the Balanced Cut problem up to value $O(\alpha)$ [MMV'12] as long as the cut $(A, B)$ has size $\Omega(\alpha)$. However, it consists of slow subroutines requiring optimal solutions for logarithmically many semidefinite programs. We study the fine-grained complexity of the problem and present the first near-linear time algorithm that achieves similar performances to that of [MMV'12]. Our algorithm runs in time $O(|V(G)|^{1+o(1)} + |E(G)|^{1+o(1)})$ and finds a balanced cut of value $O(\alpha)$. Our approach appears easily extendible to related problem, such as Sparsest Cut, and also yields an near-linear time $O(1)$-approximation to Dagupta's objective function for hierarchical clustering [Dasgupta, STOC'16] for the semi-random hierarchical stochastic block model inputs of [Cohen-Addad, Kanade, Mallmann-Trenn, Mathieu, JACM'19]., Comment: 24 pages, ICML 2024
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- 2024
17. Histopathology Foundation Models Enable Accurate Ovarian Cancer Subtype Classification
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Breen, Jack, Allen, Katie, Zucker, Kieran, Godson, Lucy, Orsi, Nicolas M., and Ravikumar, Nishant
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Large pretrained transformers are increasingly being developed as generalised foundation models which can underpin powerful task-specific artificial intelligence models. Histopathology foundation models show promise across many tasks, but analyses have been limited by arbitrary hyperparameters that were not tuned to the specific task/dataset. We report the most rigorous single-task validation conducted to date of a histopathology foundation model, and the first performed in ovarian cancer subtyping. Attention-based multiple instance learning classifiers were compared using vision transformer and ResNet features generated through varied preprocessing and pretraining procedures. The training set consisted of 1864 whole slide images from 434 ovarian carcinoma cases at Leeds Hospitals. Five-class classification performance was evaluated through five-fold cross-validation, and these cross-validation models were ensembled for evaluation on a hold-out test set and an external set from the Transcanadian study. Reporting followed the TRIPOD+AI checklist. The vision transformer-based histopathology foundation model, UNI, performed best in every evaluation, with five-class balanced accuracies of 88% and 93% in hold-out internal and external testing, compared to the best ResNet model scores of 68% and 81%, respectively. Normalisations and augmentations aided the generalisability of ResNet-based models, but these still did not match the performance of UNI, which gave the best external performance in any ovarian cancer subtyping study to date. Histopathology foundation models offer a clear benefit to subtyping, improving classification performance to a degree where clinical utility is tangible, albeit with an increased computational burden. Such models could provide a second opinion in challenging cases and may improve the accuracy, objectivity, and efficiency of pathological diagnoses overall.
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- 2024
18. A cavity-microscope for micrometer-scale control of atom-photon interactions
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Orsi, Francesca, Sauerwein, Nick, Bhatt, Rohit Prasad, Faltinath, Jonas, Fedotova, Ekaterina, Reiter, Nicola, Cantat-Moltrecht, Tigrane, and Brantut, Jean-Philippe
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Condensed Matter - Quantum Gases ,Physics - Atomic Physics - Abstract
Cavity quantum electrodynamics offers the possibility to observe and control the motion of few or individual atoms, enabling the realization of various quantum technological tasks such as quantum-enhanced metrology or quantum simulation of strongly-correlated matter. A core limitation of these experiments lies in the mode structure of the cavity field, which is hard-coded in the shape and geometry of the mirrors. As a result, most applications of cavity QED trade spatial resolution for enhanced sensitivity. Here, we propose and demonstrate a cavity-microscope device capable of controlling in space and time the coupling between atoms and light in a single-mode high-finesse cavity, reaching a spatial resolution an order-of-magnitude lower than the cavity mode waist. This is achieved through local Floquet engineering of the atomic level structure, imprinting a corresponding atom-field coupling. We illustrate this capability by engineering micrometer-scale coupling, using cavity-assisted atomic measurements and optimization. Our system forms an optical device with a single optical axis and has the same footprint and complexity as a standard Fabry-Perot cavity or confocal lens pair, and can be used for any atomic species. This technique opens a wide range of perspectives from ultra-fast, cavity-enhanced mid-circuit readout to the quantum simulation of fully connected models of quantum matter such as the Sachdev-Ye-Kitaev model.
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- 2024
19. Private graphon estimation via sum-of-squares
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Chen, Hongjie, Ding, Jingqiu, d'Orsi, Tommaso, Hua, Yiding, Liu, Chih-Hung, and Steurer, David
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Computer Science - Data Structures and Algorithms ,Computer Science - Computational Complexity ,Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
We develop the first pure node-differentially-private algorithms for learning stochastic block models and for graphon estimation with polynomial running time for any constant number of blocks. The statistical utility guarantees match those of the previous best information-theoretic (exponential-time) node-private mechanisms for these problems. The algorithm is based on an exponential mechanism for a score function defined in terms of a sum-of-squares relaxation whose level depends on the number of blocks. The key ingredients of our results are (1) a characterization of the distance between the block graphons in terms of a quadratic optimization over the polytope of doubly stochastic matrices, (2) a general sum-of-squares convergence result for polynomial optimization over arbitrary polytopes, and (3) a general approach to perform Lipschitz extensions of score functions as part of the sum-of-squares algorithmic paradigm., Comment: 71 pages, accepted to STOC 2024
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- 2024
20. An AI-enabled Agent-Based Model and Its Application in Measles Outbreak Simulation for New Zealand
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Zhang, Sijin, Orsi, Alvaro, and Chen, Lei
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Computer Science - Multiagent Systems ,Computer Science - Computers and Society ,Computer Science - Machine Learning - Abstract
Agent Based Models (ABMs) have emerged as a powerful tool for investigating complex social interactions, particularly in the context of public health and infectious disease investigation. In an effort to enhance the conventional ABM, enabling automated model calibration and reducing the computational resources needed for scaling up the model, we have developed a tensorized and differentiable agent-based model by coupling Graph Neural Network (GNN) and Long Short-Term Memory (LSTM) network. The model was employed to investigate the 2019 measles outbreak occurred in New Zealand, demonstrating a promising ability to accurately simulate the outbreak dynamics, particularly during the peak period of repeated cases. This paper shows that by leveraging the latest Artificial Intelligence (AI) technology and the capabilities of traditional ABMs, we gain deeper insights into the dynamics of infectious disease outbreaks. This, in turn, helps us make more informed decision when developing effective strategies that strike a balance between managing outbreaks and minimizing disruptions to everyday life., Comment: 11 pages, 9 figures
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- 2024
21. Max-Cut with $\epsilon$-Accurate Predictions
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Cohen-Addad, Vincent, d'Orsi, Tommaso, Gupta, Anupam, Lee, Euiwoong, and Panigrahi, Debmalya
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Computer Science - Data Structures and Algorithms ,Computer Science - Computational Complexity ,F.0 - Abstract
We study the approximability of the MaxCut problem in the presence of predictions. Specifically, we consider two models: in the noisy predictions model, for each vertex we are given its correct label in $\{-1,+1\}$ with some unknown probability $1/2 + \epsilon$, and the other (incorrect) label otherwise. In the more-informative partial predictions model, for each vertex we are given its correct label with probability $\epsilon$ and no label otherwise. We assume only pairwise independence between vertices in both models. We show how these predictions can be used to improve on the worst-case approximation ratios for this problem. Specifically, we give an algorithm that achieves an $\alpha + \widetilde{\Omega}(\epsilon^4)$-approximation for the noisy predictions model, where $\alpha \approx 0.878$ is the MaxCut threshold. While this result also holds for the partial predictions model, we can also give a $\beta + \Omega(\epsilon)$-approximation, where $\beta \approx 0.858$ is the approximation ratio for MaxBisection given by Raghavendra and Tan. This answers a question posed by Ola Svensson in his plenary session talk at SODA'23., Comment: 18 pages
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- 2024
22. Rigid clusters in shear-thickening suspensions: a nonequilibrium critical transition
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Santra, Aritra, Orsi, Michel, Chakraborty, Bulbul, and Morris, Jeffrey F.
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Condensed Matter - Soft Condensed Matter ,Condensed Matter - Statistical Mechanics - Abstract
The onset and growth of rigid clusters in a two-dimensional (2D) suspension in shear flow are studied by numerical simulation. The suspension exhibits the lubricated-to-frictional rheology transition but is studied at stresses above the levels that cause extreme shear thickening. At large solid area fraction, $\phi$, but below the jamming fraction, we find that there is critical $\phi_c$ beyond which the proportion of particles in rigid clusters grows sharply, as $f_{\rm rig} \sim (\phi-\phi_c)^{\beta}$ with $\beta=1/8$, and at which the fluctuations in the net rigidity grow sharply, with a susceptibility measure $\chi_{\rm rig} \sim |\phi-\phi_c|^{-\gamma}$ with $\gamma = 7/4$. By applying finite size scaling, the correlation length, arising from the correlation of rigid domains, is found to scale as $\xi \sim |\phi-\phi_c|^{-\nu}$ with $\nu = 1$. The system is thus found to exhibit criticality, with critical exponents consistent with the 2D Ising transition. This behavior occurs over a range of stresses, with $\phi_c$ increasing as the stress decreases, consistent with the known increase in jamming fraction with reduction of stress for shear-thickening suspensions.
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- 2024
23. IDegLira improves time in range in a cohort of patients with type 2 diabetes: TiREX study
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Malighetti, Maria Elena, Molteni, Laura, Orsi, Emanuela, Serra, Roberta, Gaglio, Alessia, Mazzoleni, Federica, Russo, Filomena, and Bossi, Antonio Carlo
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- 2024
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24. The Paradox of Modern Technology in Standardizing Thermal Liver Ablation: Fostering Uniformity or Diversity?
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Verhagen, Coosje A. M., van der Velden, Ariadne L., Bale, Reto, Bozzi, Elena, Crocetti, Laura, Denys, Alban, van Erp, Gonnie C. M., Gholamiankhah, Faeze, Greco, Giorgio, Hendriks, Pim, Knapen, Robrecht R. M. M., Kobeiter, Hicham, Lanocita, Rodolfo, Meijerink, Martijn R., Orsi, Franco, Phillips, Alice, Rahmani, Hossein, Smits, Maarten L. J., van Strijen, Marco J. L., van Dam, Ronald M., van der Leij, Christiaan, and Burgmans, Mark C.
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- 2024
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25. Association between age at diagnosis and all-cause mortality in type 2 diabetes: the Renal Insufficiency and Cardiovascular Events (RIACE) Italian Multicenter Study
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Vitale, Martina, Orsi, Emanuela, Solini, Anna, Garofolo, Monia, Grancini, Valeria, Bonora, Enzo, Fondelli, Cecilia, Trevisan, Roberto, Vedovato, Monica, Penno, Giuseppe, Nicolucci, Antonio, and Pugliese, Giuseppe
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- 2024
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26. Food contamination with fipronil alters gene expression associated with foraging in Africanized honey bees
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Lima, Yan Souza, de Castro Lippi, Isabella Cristina, da Luz Scheffer, Jaine, Lunardi, Juliana Sartori, Alvarez, Marcus Vinícius Niz, Kadri, Samir Moura, and de Oliveira Orsi, Ricardo
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- 2024
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27. First-in-human validation of a DROP-IN β-probe for robotic radioguided surgery: defining optimal signal-to-background discrimination algorithm
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Collamati, Francesco, Morganti, Silvio, van Oosterom, Matthias N., Campana, Lorenzo, Ceci, Francesco, Luzzago, Stefano, Mancini-Terracciano, Carlo, Mirabelli, Riccardo, Musi, Gennaro, Nicolanti, Francesca, Orsi, Ilaria, van Leeuwen, Fijs W. B., and Faccini, Riccardo
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- 2024
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28. Enteroaggregative Escherichia coli (EAEC) isolates obtained from non-diarrheic children carry virulence factor-encoding genes from Extraintestinal Pathogenic E. Coli (ExPEC)
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Luiz, Bruna M., Cergole-Novella, Maria C., Dantas, Stéfani T. A., de Lira, Daiany R. P., de Souza, Guilherme F. R., Fernandes, Iranildo do A., Orsi, Henrique, Solveira, Guilherme, Rall, Vera L. M., dos Santos, Luís F., and Hernandes, Rodrigo T.
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- 2024
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29. Enhanced thrombin generation induced by extracellular vesicles from severe COVID−19 cases
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Barion, Bárbara Gomes, Saito, Renata de Freitas, da Rocha, Tania Rubia Flores, Nóbrega, Thaís Dourado Reis, Okazaki, Erica, Ho, Yeh-Li, Villaça, Paula Ribeiro, Rocha, Vanderson Geraldo, and Orsi, Fernanda Andrade
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- 2024
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30. Offlabel use of Medtronic MiniMed 780G in the management of cystic fibrosis related diabetes in people requiring insulin total daily doses below 8 units: encouraging data from our population
- Author
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Grancini, Valeria, Cogliati, Irene, Gaglio, Alessia, Resi, Veronica, and Orsi, Emanuela
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- 2024
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31. Reducing Histopathology Slide Magnification Improves the Accuracy and Speed of Ovarian Cancer Subtyping
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Breen, Jack, Allen, Katie, Zucker, Kieran, Orsi, Nicolas M., and Ravikumar, Nishant
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Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Artificial intelligence has found increasing use for ovarian cancer morphological subtyping from histopathology slides, but the optimal magnification for computational interpretation is unclear. Higher magnifications offer abundant cytological information, whereas lower magnifications give a broader histoarchitectural overview. Using attention-based multiple instance learning, we performed the most extensive analysis of ovarian cancer tissue magnifications to date, with data at six magnifications subjected to the same preprocessing, hyperparameter tuning, cross-validation and hold-out testing procedures. The lowest magnifications (1.25x and 2.5x) performed best in cross-validation, and intermediate magnifications (5x and 10x) performed best in hold-out testing (62% and 61% accuracy, respectively). Lower magnification models were also significantly faster, with the 5x model taking 5% as long to train and 31% as long to evaluate slides compared to 40x. This indicates that the standard usage of high magnifications for computational ovarian cancer subtyping may be unnecessary, with lower magnifications giving faster, more accurate alternatives., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
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- 2023
32. Predicting Ovarian Cancer Treatment Response in Histopathology using Hierarchical Vision Transformers and Multiple Instance Learning
- Author
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Breen, Jack, Allen, Katie, Zucker, Kieran, Hall, Geoff, Ravikumar, Nishant, and Orsi, Nicolas M.
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition - Abstract
For many patients, current ovarian cancer treatments offer limited clinical benefit. For some therapies, it is not possible to predict patients' responses, potentially exposing them to the adverse effects of treatment without any therapeutic benefit. As part of the automated prediction of treatment effectiveness in ovarian cancer using histopathological images (ATEC23) challenge, we evaluated the effectiveness of deep learning to predict whether a course of treatment including the antiangiogenic drug bevacizumab could contribute to remission or prevent disease progression for at least 6 months in a set of 282 histopathology whole slide images (WSIs) from 78 ovarian cancer patients. Our approach used a pretrained Hierarchical Image Pyramid Transformer (HIPT) to extract region-level features and an attention-based multiple instance learning (ABMIL) model to aggregate features and classify whole slides. The optimal HIPT-ABMIL model had an internal balanced accuracy of 60.2% +- 2.9% and an AUC of 0.646 +- 0.033. Histopathology-specific model pretraining was found to be beneficial to classification performance, though hierarchical transformers were not, with a ResNet feature extractor achieving similar performance. Due to the dataset being small and highly heterogeneous, performance was variable across 5-fold cross-validation folds, and there were some extreme differences between validation and test set performance within folds. The model did not generalise well to tissue microarrays, with accuracy worse than random chance. It is not yet clear whether ovarian cancer WSIs contain information that can be used to accurately predict treatment response, with further validation using larger, higher-quality datasets required., Comment: Submission to ATEC23 challenge at MICCAI 2023 conference
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- 2023
33. An Equity-Focused Assessment of Evidence-Based Parenting Intervention Research
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Kerns, Suzanne E. U., Maddox, Samuel J., Berhanu, Ruth E., Allan, Heather, Wilson, Rachel A., Chiesa, Antonia, Orsi-Hunt, Rebecca, McCarthy, Lauren Pryce, Henry, Lesly J., and Smith, Chaundrissa Oyeshiku
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- 2024
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34. Persistent hypofibrinolysis in severe COVID-19 associated with elevated fibrinolysis inhibitors activity
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Okazaki, Erica, Barion, Bárbara Gomes, da Rocha, Tania Rubia Flores, Di Giacomo, Giovanna, Ho, Yeh-Li, Rothschild, Cynthia, Fatobene, Giancarlo, de Carvalho Moraes, Bruna del Guerra, Stefanello, Bianca, Villaça, Paula Ribeiro, Rocha, Vanderson Geraldo, and Orsi, Fernanda Andrade
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- 2024
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35. Outcomes of Extracorporeal Life Support (ECLS) in Acute Severe Asthma: A Narrative Review
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Ekechukwu, Nneoma, Batra, Sachin, Orsi, Deborah, Rahmanian, Marjan, Bangar, Maneesha, and Mohamed, Amira
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- 2024
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36. Altered functional brain networks in problematic smartphone and social media use: resting-state fMRI study
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Áfra, Eszter, Janszky, József, Perlaki, Gábor, Orsi, Gergely, Nagy, Szilvia Anett, Arató, Ákos, Szente, Anna, Alhour, Husamalddin Ali Mohammad, Kis-Jakab, Gréta, and Darnai, Gergely
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- 2024
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37. Pupillary activity in areas of interest from visual stimuli for neonatal pain assessment
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Magalhaes Jr, Roberto, Orsi, Rafael, Barros, Marina, Guinsburg, Ruth, and Thomaz, Carlos E
- Subjects
Electrical Engineering and Systems Science - Signal Processing - Abstract
This paper compares the pupillary activity index to traditional eye-tracking metrics like the fixation count and duration in assessing neonatal pain. It explores the benefits of incorporating pupillary activity measures to improve methods that lead to an understanding of cognitive processing and performance evaluation. The estimation of cognitive load using pupil diameter typically involves measures relative to a baseline. Instead, we conducted an eye-tracking study using the Low/High Index of Pupillary Activity to evaluate healthcare experts and non-experts analyzing the faces with and without pain from a dataset of newborn faces. This data was recorded by the Tobii TX300 eye-tracking system in a closed room with controlled lighting. Our contribution is to introduce the LHIPA calculation considering the areas of interest segments of the pupil diameter signal. The results suggest that the visual attention reflected by the traditional metrics may not correspond directly to the respective cognitive load for both sample groups of participants.
- Published
- 2023
38. Generative Adversarial Networks for Stain Normalisation in Histopathology
- Author
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Breen, Jack, Zucker, Kieran, Allen, Katie, Ravikumar, Nishant, and Orsi, Nicolas M.
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
The rapid growth of digital pathology in recent years has provided an ideal opportunity for the development of artificial intelligence-based tools to improve the accuracy and efficiency of clinical diagnoses. One of the significant roadblocks to current research is the high level of visual variability across digital pathology images, causing models to generalise poorly to unseen data. Stain normalisation aims to standardise the visual profile of digital pathology images without changing the structural content of the images. In this chapter, we explore different techniques which have been used for stain normalisation in digital pathology, with a focus on approaches which utilise generative adversarial networks (GANs). Typically, GAN-based methods outperform non-generative approaches but at the cost of much greater computational requirements. However, it is not clear which method is best for stain normalisation in general, with different GAN and non-GAN approaches outperforming each other in different scenarios and according to different performance metrics. This is an ongoing field of study as researchers aim to identify a method which efficiently and effectively normalises pathology images to make AI models more robust and generalisable., Comment: Updated to add link to full publication at https://doi.org/10.1007/978-3-031-46238-2_11
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- 2023
39. Data-driven Predictive Latency for 5G: A Theoretical and Experimental Analysis Using Network Measurements
- Author
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Skocaj, Marco, Conserva, Francesca, Grande, Nicol Sarcone, Orsi, Andrea, Micheli, Davide, Ghinamo, Giorgio, Bizzarri, Simone, and Verdone, Roberto
- Subjects
Computer Science - Networking and Internet Architecture ,Computer Science - Machine Learning - Abstract
The advent of novel 5G services and applications with binding latency requirements and guaranteed Quality of Service (QoS) hastened the need to incorporate autonomous and proactive decision-making in network management procedures. The objective of our study is to provide a thorough analysis of predictive latency within 5G networks by utilizing real-world network data that is accessible to mobile network operators (MNOs). In particular, (i) we present an analytical formulation of the user-plane latency as a Hypoexponential distribution, which is validated by means of a comparative analysis with empirical measurements, and (ii) we conduct experimental results of probabilistic regression, anomaly detection, and predictive forecasting leveraging on emerging domains in Machine Learning (ML), such as Bayesian Learning (BL) and Machine Learning on Graphs (GML). We test our predictive framework using data gathered from scenarios of vehicular mobility, dense-urban traffic, and social gathering events. Our results provide valuable insights into the efficacy of predictive algorithms in practical applications.
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- 2023
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40. Co-detection of respiratory pathogens among ILI patients: characterization of samples collected during the 2018/19 and 2019/20 pre-pandemic seasons
- Author
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Allegra Ferrari, Irene Schiavetti, Matilde Ogliastro, Carola Minet, Raffaella Sibilio, Irene Giberti, Elisabetta Costa, Elvira Massaro, Piero Luigi Lai, Stefano Mosca, Bianca Bruzzone, Andrea Orsi, Donatella Panatto, and Giancarlo Icardi
- Subjects
Co-infection ,Respiratory tract infection ,Respiratory pathogens ,LRI ,URI ,Syndromic surveillance ,Infectious and parasitic diseases ,RC109-216 - Abstract
Abstract Influenza-like illness (ILI) patients co-detected with respiratory pathogens exhibit poorer health outcomes than those with single infections. To address the paucity of knowledge concerning the incidence of concurrent respiratory pathogens, their relationships, and the clinical differences between patients detected with single and multiple pathogens, we performed an in-depth characterization of the oropharyngeal samples of primary care patients collected in Genoa (Northwest Italy), during winter seasons 2018/19–2019/20. The apriori algorithm was employed to evaluate the incidence of viral, bacterial, and viral-bacterial pairs during the study period. The grade of correlation between pathogens was investigated using the Phi coefficient. Factors associated with viral, bacterial or viral-bacterial co-detection were assessed using logistic regression. The most frequently identified pathogens included influenza A, rhinovirus, Haemophilus influenzae and Streptococcus pneumoniae. The highest correlations were found between bacterial-bacterial and viral-bacterial pairs, such as Haemophilus influenzae-Streptococcus pneumoniae, adenovirus-Haemophilus influenzae, adenovirus-Streptococcus pneumoniae, RSV-A-Bordetella pertussis, and influenza B Victoria-Bordetella parapertussis. Viruses were detected together at significantly lower rates. Notably, rhinovirus, influenza, and RSV exhibited significant negative correlations with each other. Co-detection was more prevalent in children aged
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- 2024
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41. Declining number of general practitioners can impair influenza vaccination uptake among Italian older adults: Results from a panel analysis
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Alexander Domnich, Francesco Lapi, Andrea Orsi, Ignazio Grattagliano, Alessandro Rossi, Claudio Cricelli, and Giancarlo Icardi
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Influenza ,Vaccination ,General practitioner ,Older adults Italy ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background Seasonal influenza vaccination coverage in Italian older adults is insufficient and well below the minimum target of 75%. In Italy, most influenza vaccine doses are administered by general practitioners (GPs), whose number has been declining. In parallel, the number of patients per GP and GP workload increased dramatically, which theoretically may impair vaccination counselling. In this ecological study, we aimed to assess whether influenza vaccination coverage in older adults is associated with the density of GPs having high number of patients. Methods The study outcome was the influenza vaccination coverage rate in adults aged ≥ 65 years and registered in 20 Italian regions over the last 23 years. The independent variable of interest was the proportion of GPs with more than 1,500 adult patients, which is an imposed normative ceiling. This latter variable was considered as a proxy of GP overload. By adopting a panel regression approach, different specifications of fixed- and random-effects models were run to assess the association of interest, when adjusted for several social structural, economic and healthcare-related variables. Results Over the last two decades, most regions showed a negative association between influenza vaccination coverage rates and the density of GPs with a high number of patients. This latter negative association was confirmed (P
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- 2024
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42. On the relationship between δO2∕N2 variability and ice sheet surface conditions in Antarctica
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R. Harris Stuart, A. Landais, L. Arnaud, C. Buizert, E. Capron, M. Dumont, Q. Libois, R. Mulvaney, A. Orsi, G. Picard, F. Prié, J. Severinghaus, B. Stenni, and P. Martinerie
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Environmental sciences ,GE1-350 ,Geology ,QE1-996.5 - Abstract
While the processes controlling pore closure are broadly understood, the physical mechanisms driving the associated elemental fractionation remains ambiguous. Previous studies have shown that the pore closure process leads to a depletion in small-sized molecules (e.g. H2, O2, Ar, Ne, He) in ice core bubbles relative to larger-sized molecules like N2. This size-dependent fractionation, identified using ice core δ(O2/N2) records, exhibits a clear anti-correlation with local summer solstice insolation, making δ(O2/N2) a valuable ice core dating tool. Mechanisms controlling this relationship are attributed to the physical properties of deep firn. In this study, we compile δ(O2/N2) records from 15 polar ice cores and show a new additional link between δ(O2/N2) and local surface temperature and/or accumulation rate. Using the Crocus snowpack model, we perform sensitivity tests to identify the response of near-surface snow properties to changes in insolation intensity, accumulation rate, and air temperature. These tests support a mechanism linked to firn grain size, such that the larger the grain size for a given density, the stronger the pore closure fractionation and, hence, the lower the δ(O2/N2) values archived in the ice. Based on both snowpack model outputs and data compilation, our findings suggest that local accumulation rate and temperature should be considered when interpreting δ(O2/N2) as a local insolation proxy.
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- 2024
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43. Reaching Kesten-Stigum Threshold in the Stochastic Block Model under Node Corruptions
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Ding, Jingqiu, d'Orsi, Tommaso, Hua, Yiding, and Steurer, David
- Subjects
Computer Science - Machine Learning ,Computer Science - Social and Information Networks ,Statistics - Machine Learning - Abstract
We study robust community detection in the context of node-corrupted stochastic block model, where an adversary can arbitrarily modify all the edges incident to a fraction of the $n$ vertices. We present the first polynomial-time algorithm that achieves weak recovery at the Kesten-Stigum threshold even in the presence of a small constant fraction of corrupted nodes. Prior to this work, even state-of-the-art robust algorithms were known to break under such node corruption adversaries, when close to the Kesten-Stigum threshold. We further extend our techniques to the $Z_2$ synchronization problem, where our algorithm reaches the optimal recovery threshold in the presence of similar strong adversarial perturbations. The key ingredient of our algorithm is a novel identifiability proof that leverages the push-out effect of the Grothendieck norm of principal submatrices.
- Published
- 2023
44. Private Graphon Estimation via Sum-of-Squares.
- Author
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Hongjie Chen, Jingqiu Ding, Tommaso d'Orsi, Yiding Hua, Chih-Hung Liu 0001, and David Steurer
- Published
- 2024
- Full Text
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45. Organic Human-Robot Interactions: Psychological Aspects to Help Social Robots Become Sociable.
- Author
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Balázs Orsi, Csilla Csukonyi, and Péter Korondi
- Published
- 2024
- Full Text
- View/download PDF
46. What Is a Good Model? : With Examples from Endocrinology
- Author
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Panunzi, Simona, Pompa, Marcello, Borri, Alessandro, D’Orsi, Laura, De Gaetano, Andrea, Castro, Carlos, Editor-in-Chief, Formaggia, Luca, Editor-in-Chief, Groppi, Maria, Series Editor, Larson, Mats G., Series Editor, Lopez Fernandez, Maria, Series Editor, Morales de Luna, Tomás, Series Editor, Pareschi, Lorenzo, Series Editor, Vázquez-Cendón, Elena, Series Editor, Zunino, Paolo, Series Editor, d'Onofrio, Alberto, editor, Fasano, Antonio, editor, Papa, Federico, editor, Sinisgalli, Carmela, editor, Bertuzzi, Alessandro, Foreword by, Pettorossi, Alberto, Foreword by, and Gandolfi, Riccardo, Foreword by
- Published
- 2024
- Full Text
- View/download PDF
47. Generative Adversarial Networks for Stain Normalisation in Histopathology
- Author
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Breen, Jack, Zucker, Kieran, Allen, Katie, Ravikumar, Nishant, Orsi, Nicolas M., and Lyu, Zhihan, editor
- Published
- 2024
- Full Text
- View/download PDF
48. Co-detection of respiratory pathogens among ILI patients: characterization of samples collected during the 2018/19 and 2019/20 pre-pandemic seasons
- Author
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Ferrari, Allegra, Schiavetti, Irene, Ogliastro, Matilde, Minet, Carola, Sibilio, Raffaella, Giberti, Irene, Costa, Elisabetta, Massaro, Elvira, Lai, Piero Luigi, Mosca, Stefano, Bruzzone, Bianca, Orsi, Andrea, Panatto, Donatella, and Icardi, Giancarlo
- Published
- 2024
- Full Text
- View/download PDF
49. Declining number of general practitioners can impair influenza vaccination uptake among Italian older adults: Results from a panel analysis
- Author
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Domnich, Alexander, Lapi, Francesco, Orsi, Andrea, Grattagliano, Ignazio, Rossi, Alessandro, Cricelli, Claudio, and Icardi, Giancarlo
- Published
- 2024
- Full Text
- View/download PDF
50. Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand
- Author
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Watson, Leighton M., Plank, Michael J., Armstrong, Bridget A., Chapman, Joanne R., Hewitt, Joanne, Morris, Helen, Orsi, Alvaro, Bunce, Michael, Donnelly, Christl A., and Steyn, Nicholas
- Published
- 2024
- Full Text
- View/download PDF
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